Systems, devices, and/or processes for omic content processing and/or partitioning

ABSTRACT

Subject matter disclosed herein may relate to at least one processor to selectively authorize requests from one or more external devices to read from and/or write to particular bio-ledger entries and/or particular biosphere ledger entries based, at least in part, on security tokens provided by the one or more external devices and based, at least in part, on first and/or second sets of particular authorizations.

RELATED APPLICATIONS

This patent application is related to U.S. Ser. No. 15/922,721 entitledSystems, Devices, and/or Processes for Omic and/or Behavioral ContentProcessing; U.S. Ser. No. 15/922,738 entitled Systems, Devices, and/orProcesses for Omic Content Processing and/or Communication; and U.S.Ser. No. 15/922,771 entitled Systems, Devices, and/or Processes for OmicContent and/or Environmental Content Processing and/or Communication;all filed concurrently with this patent application, and all herebyincorporated by reference in their entirety.

BACKGROUND Field

Subject matter disclosed herein relates to systems, devices, and/orprocesses for processing and/or partitioning signals and/or statesrepresentative of omic content.

Information

Integrated circuit devices, such as processors, for example, may befound in a wide range of electronic device types. For example, one ormore processors may be used in mobile devices, such as cellular phones,for example, as well as in server computers, personal computers, digitalcameras, tablet devices, personal digital assistants, wearable devices,etc. Mobile devices and/or other computing devices, for example, mayinclude integrated circuit devices, such as processors, to processsignals and/or states representative of a diverse of content types for avariety of purposes. With an abundance of diverse content beingaccessible, signal and/or state processing techniques continue toevolve. At times, however, processing signals and/or statesrepresentative of diverse content may prove to be relativelyresource-demanding, which may present a number of challenges including,for example, increased processing time, storage demands, complexity,cost, and/or the like.

BRIEF DESCRIPTION OF THE DRAWINGS

Claimed subject matter is particularly pointed out and distinctlyclaimed in the concluding portion of the specification. However, both asto organization and/or method of operation, together with objects,features, and/or advantages thereof, it may best be understood byreference to the following detailed description if read with theaccompanying drawings in which:

FIG. 1 is an illustration depicting an example DNA portion, inaccordance with an embodiment.

FIG. 2 is an illustration of an example process for detecting a changein epigenetic state, in accordance with an embodiment.

FIG. 3a is a schematic block diagram depicting an example device,system, and/or process for communication and/or processing of epigeneticcontent, in accordance with an embodiment.

FIG. 3b is a schematic block diagram depicting an example communicationof parameters between a storage device and an intermediary device, inaccordance with an embodiment.

FIG. 3c is a schematic block diagram depicting an example communicationof parameters between an intermediary device and a bio-smart device, inaccordance with an embodiment.

FIG. 3d is a schematic block diagram depicting an example device,system, and/or process for communication of epigenetic content, inaccordance with an embodiment.

FIG. 4 is an illustration of an example storage device, in accordancewith an embodiment.

FIG. 5 is an illustration of an example process for initiatingcommunication of parameters to an intermediary device, in accordancewith an embodiment.

FIG. 6 is an illustration of an example process for initiatingcommunication of epigenetic content parameters, in accordance with anembodiment.

FIG. 7 is an illustration of an example intermediary device, inaccordance with an embodiment.

FIG. 8 is an illustration of an example process for initiatingcommunication of parameters to a bio-smart device, in accordance with anembodiment.

FIG. 9 is an illustration of an example bio-smart device, in accordancewith an embodiment.

FIG. 10 is an illustration of an example process for detecting and/orpredicting a change in epigenetic state, in accordance with anembodiment.

FIG. 11 is an illustration of an example device, system, and/or processfor processing signals and/or states representative of epigeneticcontent and/or behavioral content, in accordance with an embodiment.

FIG. 12 is an illustration of an example device, system, and/or processfor processing signals and/or states representative of epigeneticcontent and/or behavioral content, in accordance with an embodiment.

FIG. 13 is an illustration of an example device, system, and/or processfor processing signals and/or states representative of epigeneticcontent and/or behavioral content, in accordance with an embodiment.

FIG. 14 is an illustration of an example process for generatingrecommendations directed to improvement of a future epigenetic fitnessstate of a particular individual, in accordance with an embodiment.

FIG. 15a is an illustration of an example logging-type device, inaccordance with an embodiment.

FIG. 15b is an illustration of an example communication of epigeneticcontent between a logging-type device and a storage device, inaccordance with an embodiment.

FIG. 16 is an illustration of an example device, system, and/or processfor processing signals and/or states representative of epigeneticcontent, in accordance with an embodiment.

FIG. 17 is an illustration of an example process for detecting locationsassociated with undesirable changes in epigenetic state, in accordancewith an embodiment.

FIG. 18 is an illustration of an example process for identifyingpatterns of changes in epigenetic, microbiome, and/or proteomeparameters, in accordance with an embodiment.

FIG. 19 is a schematic block diagram of an example computing device, inaccordance with an embodiment.

Reference is made in the following detailed description to accompanyingdrawings, which form a part hereof, wherein like numerals may designatelike parts throughout that are corresponding and/or analogous. It willbe appreciated that the figures have not necessarily been drawn toscale, such as for simplicity and/or clarity of illustration. Forexample, dimensions of some aspects may be exaggerated relative toothers. Further, it is to be understood that other embodiments may beutilized. Furthermore, structural and/or other changes may be madewithout departing from claimed subject matter. References throughoutthis specification to “claimed subject matter” refer to subject matterintended to be covered by one or more claims, or any portion thereof,and are not necessarily intended to refer to a complete claim set, to aparticular combination of claim sets (e.g., method claims, apparatusclaims, etc.), or to a particular claim. It should also be noted thatdirections and/or references, for example, such as up, down, top,bottom, and so on, may be used to facilitate discussion of drawings andare not intended to restrict application of claimed subject matter.Therefore, the following detailed description is not to be taken tolimit claimed subject matter and/or equivalents.

DETAILED DESCRIPTION

References throughout this specification to one implementation, animplementation, one embodiment, an embodiment, and/or the like meansthat a particular feature, structure, characteristic, and/or the likedescribed in relation to a particular implementation and/or embodimentis included in at least one implementation and/or embodiment of claimedsubject matter. Thus, appearances of such phrases, for example, invarious places throughout this specification are not necessarilyintended to refer to the same implementation and/or embodiment or to anyone particular implementation and/or embodiment. Furthermore, it is tobe understood that particular features, structures, characteristics,and/or the like described are capable of being combined in various waysin one or more implementations and/or embodiments and, therefore, arewithin intended claim scope. In general, of course, as has always beenthe case for the specification of a patent application, these and otherissues have a potential to vary in a particular context of usage. Inother words, throughout the patent application, particular context ofdescription and/or usage provides helpful guidance regarding reasonableinferences to be drawn; however, likewise, “in this context” in generalwithout further qualification refers to the context of the presentpatent application.

As mentioned, integrated circuit devices, such as processors, forexample, may be found in a wide range of electronic device types. Forexample, one or more processors may be used in mobile devices, such astablet devices and/or cellular phones, for example, as well as in servercomputers, personal computers, digital cameras, tablet devices, personaldigital assistants, wearable devices, etc. Mobile devices and/or othercomputing devices, for example, may include integrated circuit devices,such as processors, to process signals and/or states representative of adiverse of content types for a variety of purposes. With an abundance ofdiverse content being accessible, signal and/or state processingtechniques continue to evolve. At times, however, processing signalsand/or states representative of diverse content may prove to berelatively resource-demanding, which may present a number of challengesincluding, for example, increased processing time, storage demands,complexity, cost, and/or the like.

In some circumstances, integrated circuit devices, such as processors,for example, may be employed in computing devices, for example, toperform tasks that may be beneficial in managing and/or improving abiological, behavioral, and/or emotional state of an individual. Forexample, embodiments may analyze and/or otherwise process epigeneticcontent and/or other content types (e.g., parameters indicative ofenvironmental factors, behavioral factors, etc.) to detect and/orpredict changes in an epigenetic state for a particular individual. Insome embodiments, potentially undesirable changes in epigenetic statemay be detected and/or predicted, and/or recommendations may begenerated with a goal of improving an epigenetic state of a particularindividual.

“Omics” and/or the like generally refers to biological fields of study,such as genomics, proteomics, metabolomics, epigenomics, microbiomics,etc. Herein, “omic content” and/or the like refers to epigenetic,microbiome, proteome, metabolome, or transcriptome content, or anycombination thereof. Embodiments may also involve genomic content.“Epigenetic content” refers to signals and/or states representative ofone or more epigenetic parameters. Epigenetic and/or other omic content,for example, may be transmitted and/or received as signals and/or states(e.g., signal packets) physically propagated over a network, such as theInternet. Further, epigenetic and/or other omic content may be stored assignals and/or states in a memory, for example. “Epigenetic” in somecases and/or contexts refers to bio-markers that may sit on top ofparticular genes within animal, such as human, and/or plantdeoxyribonucleic acid (DNA). Further, in some cases, epigeneticbio-markers may be measured through a technique similar to geneticsequencing. Epigenetic parameters, for example, may be representative ofone or more particular bio-markers that may result in a particular geneexpression (e.g., which particular genes are turned on and/or turnedoff). For example, a bio-marker may sit on top of a genome and maychange that particular genome's function. Example mechanisms forchanging a genome's function may include, but are not limited to,attachment of a methyl group comprising a carbon atom and three carbonatoms (CH₃) to one or more segments of DNA, and/or histone modification.Epigenetic mechanisms may encompass a number of pre-transcriptional topost-translational events involving chromatin structure, methylation,non-coding ribonucleic acids (RNA), and/or histone modification, forexample. Subject matter is not limited in scope in these regards.

FIG. 1, for example, depicts an example illustration 100 of an exampleDNA portion, such as DNA portion 100. As depicted in FIG. 1, an exampleDNA portion, such as DNA portion 110, may include example histones 120and/or example histone tails 130. Histones, such as example histones120, may comprise proteins around which DNA may wind, such as forcompaction and/or gene regulation, for example. Histone modification mayinvolve, in some circumstances, the binding of epigenetic factors, suchas example epigenetic factors 140, to histone tails, such as examplehistone tails 130. For example, a binding of epigenetic factors tohistone tails may alter an extent to which DNA may be wrapped aroundhistones and/or may alter an extent to which the availability of genes,such as example genes 150 and/or 160, in the DNA may be activated. Forexample, one or more epigenetic factors 140 may bind to one or morehistone tails 130, and as a result, at least in part, one or more genes150 may be deactivated.

Additionally, DNA methylation may occur, for example, in response tomethyl groups (e.g., as produced by the body and/or consumed in somedietary source, such as in the form of 5-methyltetrahydrofolate) taggingDNA and/or activating and/or repressing particular genes. Epigeneticmechanisms may be affected at least in part by any of several examplefactors and/or processes including, but not limited to, development inutero and/or in childhood, environmental chemicals, drugs and/orpharmaceuticals, aging, diet, etc. Epigenetic factors and/or processesmay generally have an effect on people's health, potentially resultingin some situations in cancer, autoimmune disease, mental disorders,and/or diabetes, to name but a few examples. The term “exposome” mayrefer to a measure of cumulative exposures of an individual over thecourse of a lifetime and/or how those exposures may relate to the healthof an individual. An individual's exposure may begin before birth and/ormay include effects from environmental and/or occupational sources, forexample. Such exposure may influence, for example, epigenome,microbiome, proteome, metabolome, transcriptome, and/or other statesthat may impact, adversely and/or otherwise, an individual's healthand/or wellbeing.

While an individual's genes typically may not change during a lifetime,epigenetic bio-markers, such as example epigenetic factors 140, maychange based at least in part on environmental factors in somecircumstances. For example, epigenetic changes may occur due at least inpart to climate, diet, exercise, environmental toxins, etc. Science hasdetermined some epigenetic indicators of particular diseases, such asvarious cancers and/or diabetes, as well as epigenetic indicators ofsocietally-relevant conditions such as addiction, risk of suicide, etc.,for example. Further, science has determined that at least someepigenetic characteristics may be transferred from individuals to theiroffspring in a process referred to as “epigenetic inheritance” and/or“transgenerational epigenetic inheritance.”

Although some embodiments described herein mention epigenetic content,embodiments are not restricted to epigenetic content, but rather mayinclude other “omic” content. As mentioned, “omics” and/or the like inthis context generally refers to biological fields of study, such asgenomics, proteomics, metabolomics, epigenomics, microbiomics, etc.Herein, “omic content” and/or the like refers to epigenetic, microbiome,proteome, metabolome, or transcriptome content, or any combinationthereof. As also mentioned, embodiments may also involve genomiccontent. In an embodiment, as more detailed and/or comprehensiveepigenetic and/or other omic content becomes available for individuals,it may be beneficial to make such content, and/or particular portions ofsuch content, available to electronic devices configured to processepigenetic and/or other omic content to an individual's benefit, forexample. In an embodiment, for example, it may be advantageous to havean electronic device determine what particular levels of body fat may beharmless for a particular individual. For another example, it may bebeneficial to have an electronic device detect whether a decline incognitive function may be a result of fatigue and/or whether a declinemay be a result of early-onset dementia. In a further example, it may beadvantageous for an electronic device to determine whether a change inepigenetic markers may be presaged by changes in particular airparticulates and/or by an introduction of different dietary elements.Challenges related to implementing such devices, systems, and/orprocesses may include, for example, enabling electronic devices toaccess particular sensitive, private, and/or confidential content whileachieving a desired level of security in storing and/or communicatingsensitive, private, and/or confidential content. An additional examplechallenge may include development of a recommended, standardized, and/orotherwise specified manner of tracking, monitoring, storing, and/orrepresenting, for example, an individual's environmental influencerssuch that science and/or analytics, for example, may continue todetermine relationships and/or correlations between an individual'senvironmental factors and changes in personal biological content, forexample.

Embodiments may include devices, systems, and/or processes forrelatively securely storing content, such as epigenetic and/or otheromic content, for one or more particular individuals and/or forrelatively securely communicating content, such as epigenetic content,to various devices, for example. Example embodiments described hereinmay further be directed to devices, systems, and/or processes that mayenable, at least in part, and/or may include, one or more “bio-smart”devices. “Bio-smart,” and/or “bio-smart device” and/or the like refer tothe use of personal biological (e.g., omic) content by a computingdevice, for example, to help manage and/or improve a biological,behavioral, and/or emotional state of an individual. As described morefully below, bio-smart devices may, in embodiments, interact with anindividual's bio-ledger and/or biosphere ledger in a relatively securemanner. In embodiments, a bio-smart device may relatively securelyinteract with an individual's bio-ledger and/or biosphere ledger withhelp from an intermediary device, as also explained more fully below.For bio-smart devices, interactions with an individual's bio-ledgerand/or biosphere ledger may include, for example, reading and/orwriting. By contrast, logging-type devices, more fully described below,may write content (e.g., environmental measurement parameters) to astorage device, such as secure storage device, but may not, in anembodiment, read from a bio-ledger and/or biosphere ledger. In anembodiment, as described more fully below, a logging-type device maywrite content to a secure storage device, for example, and the securestorage device may store obtained content in one or more individual'sbio-ledger and/or biosphere ledger. A secure storage device may also,for example, store satellite positioning system (e.g., GPS) locationparameters associated with content obtained from a logging-type devicein one or more individual's bio-ledger and/or biosphere ledger.Embodiments may employ machine learning and/or other content analytictechniques to leverage personal biological content, such as epigeneticand/or other omic content, for example, to help, at least in part, oneor more particular individuals to improve their biological, behavioral,and/or motional states.

Embodiments may enable electronic devices, such as bio-smart devices, torequest and/or access subsets of personal biological content measured,determined, and/or otherwise gathered at one or more previous points intime, for example. Embodiments may further include coordinated and/ortimestamped snapshots of an individual's biological content and/orcontent representative of environmental influencers to enable, at leastin part, additional understanding of relationships and/or correlationsbetween changes in biological state of an individual and environmentalinfluencers, for example. Further, embodiments may include aggregationof an individual's biological and/or environmental influencer content,for example, that may result at least in part from an increase innumbers of environmental sensors and/or an increase in particularmedical testing. In an embodiment, content may be aggregated in arecommended, standardized, and/or otherwise specified manner, forexample.

For example, in an embodiment, epigenetic and/or other omic content(e.g., microbiome, proteome, metabolome, and/or transcriptome content)pertaining to a particular individual may be obtained, wherein theepigenetic and/or other omic content may be representative of one ormore particular epigenetic and/or other omic states for the particularindividual at respective points in time. In an embodiment, epigeneticcontent may include parameters indicative of particular bio-markersassociated with particular gene expressions, for example. Embodimentsmay analyze and/or otherwise process epigenetic content and/or othercontent types (e.g., parameters indicative of environmental factors,behavioral factors, etc.) to detect and/or predict changes in epigeneticstate for a particular individual. In some embodiments, potentiallyundesirable changes in epigenetic state may be detected and/orpredicted, and/or recommendations may be generated with a goal ofimproving an epigenetic state of a particular individual. As mentioned,although embodiments may, for ease of discussion, describe epigeneticcontent, claimed subject matter is not limited in scope in this respect.For example, embodiments may include epigenetic, microbiome, proteome,metabolome, or transcriptome content, or any combination thereof.

In at least some embodiments, content, such as may be obtained from oneor more sensors, for example, may be processed to generate content, suchas behavioral profile content, for one or more individuals. Inembodiments, behavioral profile content may be analyzed and/or otherwiseprocessed in combination with epigenetic content, for example, to detectand/or predict changes in epigenetic state for one or more individuals.Further, in embodiments, content, such as behavioral profile content forone or more individuals, may be analyzed and/or otherwise processed incombination with epigenetic content, for example, to generaterecommendations with respect to one or more individuals. In embodiments,recommendations may be directed at improving a current and/or futureepigenetic state of one or more individuals. In other embodiments,content, such as behavioral profile content for a particular individual,may be analyzed and/or otherwise processed in combination withepigenetic content, for example, to generate recommendations for aparticular individual directed to the particular individual's behavioraland/or biological state.

In an embodiment, content obtained from one or more sensors may beprocessed by particular hardware circuitry to generate behavioralprofile content representative of a particular individual's physical,mental, and/or emotional state. For example, a processor, such as abehavioral processing unit, may be dedicated, at least in part, toprocessing sensor content to generate behavioral profile contentrepresentative of a particular individual's physical, mental, and/oremotional state. A processor, such as a behavioral processing unit, mayinclude particular circuitry directed to performing particularoperations to relatively more efficiently process sensor content togenerate behavioral profile content for a particular individual, in anembodiment. For example, in an embodiment, a processor, such as abehavioral processing unit, may include machine learning accelerationcircuitry directed to performing particular operations that mayrelatively more efficiently operate on sets of parameters, such asmulti-dimensional sets of parameters, that may be utilized in variousmachine learning techniques such as, for example, neural networks, asdiscussed more fully below. In an embodiment, a processor, such as abehavioral processing unit, may comprise a co-processor, for example,that may operate in cooperation with a general-purpose processor,although subject matter is not limited in this respect.

The terms “individual,” “operator,” and/or “user” refer to humanindividuals and/or may be utilized herein interchangeably. In somecontexts, such as related to agricultural applications, an “individual”may comprise a particular plant, crop, and/or farm, for example.Further, as utilized herein, “behavioral profile content” and/or thelike refers to one or more parameters representative of a behavioral,physical, mental, and/or emotional state for at least one particularindividual (e.g., human and/or plant). Thus, for example, “behavioralprofile content” and/or the like is not limited to merely behavioralaspects of a particular individual's state, but may also includeparameters representative of one or more biological aspects with respectto a particular individual, as explained more fully herein. Further,although some embodiments herein may be described in connection with“an” individual and/or “a” particular individual, subject matter is notlimited to a single individual. For example, at least some embodimentsmay include behavioral profile content for one or more individuals,although, again, subject matter is not limited in scope in theserespects. Also, content refers to physical signals and/or states thatmay be transmitted and/or received, for example, via wired and/orwireless interconnects and/or via one or more networks. Signals andstates comprising content may also be stored in a memory and/or a massstorage device, for example. Example communication technologies and/orexample physical media by which content, such as omic and/or behavioralprofile content, may be transmitted, received, and/or stored, forexample, are mentioned below.

Further, as utilized herein, the term “current” and/or the like refersto substantially and/or approximately current with respect to a point intime. For example, a “current” behavioral and/or biological state of aparticular individual refers to a behavioral and/or biological state forthe particular individual derived at least in part from relativelyrecent sensor content. For example, in an embodiment, behavioral profilecontent for a particular individual may be representative of abehavioral and/or biological state of the particular individual derivedat least in part from sensor content obtained from one or more sensorswithin fractions of a second of being generated.

FIG. 2 is an illustration of an example process for detecting a changein epigenetic state, in accordance with an embodiment. Embodiments inaccordance with claimed subject matter may include all of blocks210-270, fewer than blocks 210-270, and/or more than blocks 210-270.Further, the order of blocks 210-270 is merely an example order, andsubject matter is not limited in scope in these respects. As depicted atblocks 210 and/or 220, epigenetic content, such as in the form ofbio-ledger content and/or biosphere ledger content, may be gatheredand/or otherwise obtained for one or more individuals. In an embodiment,an electronic device, such as a bio-smart device and/or a secure storagedevice, as discussed more fully below, may receive signals and/or statescomprising omic content, for example, from one or more devices. In anembodiment, content, such as omic content, may be transmitted and/orreceived via wired and/or wireless network connections. For example,omic content, such as bio-ledger content and/or biosphere ledgercontent, may be transmitted and/or received via signal packetcommunications and/or signal frame communications, also referred to assignal packet transmissions and/or signal frame transmissions (or merely“signal packets” or “signal frames”). In an embodiment, signal packetsand/or signal frames, for example, may be communicated between nodes ofa network, where a node may comprise one or more network devices and/orone or more computing devices, for example. As discussed more fullybelow, epigenetic content and/or other content types, such as behavioralprofile content, may be analyzed and/or otherwise processed at least inpart to detect and/or predict changes in epigenetic state for one ormore individuals. In an embodiment, a computing device may include oneor more processors, such as one or more behavioral processing units,discussed below. In an embodiment, behavioral profile content may bewritten to an individual's bio-ledger and/or biosphere ledger, which mayinclude a computing device, such as a bio-smart device, transmitting viasignal packet communication and/or signal frame communication, forexample, parameters representative of omic content to be stored at asecure storage device. Further, in an embodiment, epigenetic and/orother omic content may be processed via one or more processors at leastin part to detect and/or predict changes in epigenetic state, asexplained more fully below.

To analyze and/or otherwise process epigenetic content, a device,system, and/or process may request subsets of epigenetic content for oneor more particular individuals from previous points in time. Machinelearning and/or other analytic techniques may benefit from generation ofcoordinated and/or time-stamped snapshots of a individual's epigeneticcontent and/or time-stamped snapshots of a individual's behavioralprofile content, and/or may also benefit from coordinated and/ortime-stamped snapshots of environmental factors corresponding to aindividual's epigenetic content. Embodiments may further employenvironmental sensors and/or medical (e.g., genetic, biological, etc.)testing to gather, over a period of time, epigenetic content and/orcontent representative of environmental factors for one or moreindividuals. In an embodiment, epigenetic and/or other omic content maybe gathered, for example, by receiving signals and/or states at acommunication interface of an electronic device and/or by storing thereceived signals and/or states in a non-transitory memory. Epigeneticand/or environmental content for one or more individuals may beconfigured in a manner relatively more conducive to identification ofrelationships, correlations, etc. between epigenetic changes and/orenvironmental factors. As mentioned, embodiments are not restricted toepigenetic content, but may also include other types of omic content(e.g., microbiome, proteome, metabolome, and/or transcriptome content).

For example, as suggested at blocks 210 and/or 220, personal bio-ledgersand/or personal biosphere ledgers may be generated from epigenetic,and/or environmental content for a particular individual. As utilizedherein, “Bio-ledger” refers to entries of parameters representative ofone or more aspects of one or more individual's internal biologicalstate stored in at least one non-transitory medium and/or memory of atleast one computing device. In an embodiment, bio-ledger entries may betime-stamped. For example, time-stamped entries may correspond, at leastin part, to one or more aspects of an individual's internal biologicalstate at particular points in time, for example. In an embodiment,bio-ledger entries may include parameters representative of one or moreaspects of genetic content, epigenetic content, microbiome content, orproteome content, metabolome content, and/or transcriptome content, orany combination thereof, to name several non-limiting examples.Bio-ledger entries may further include, for example, lab test contentfor an individual, content representative of diagnosed diseases for anindividual, identified risk factors for an individual, etc. In anembodiment, a bio-ledger may include entries for any number ofparticular individuals and/or for a population of individuals, forexample. In an embodiment, a bio-ledger may be indexed within at leastone memory of a computing device on a per-individual basis. Further,particular individuals may be associated with more than one bio-ledgerand/or biosphere ledger. For example, different bio-ledgers and/orbiosphere ledgers for an individual may incorporate varying securitycharacteristics and/or permissions, in an embodiment.

Further, as utilized herein, “biosphere ledger” refers to entries ofparameters representative of one or more environmental aspects relatedto one or more particular individuals stored in at least onenon-transitory medium and/or memory of at least one computing device.Environmental aspects may include, for example, environmental exposures(e.g., air and/or water pollutants), lifestyle (e.g., media consumption,diet, exercise, medications, etc.), and/or behavioral (e.g., behavioralprofile content). “Environmental content” refers to one or moreparameters indicative of one or more particular environmental aspectsrelated to one or more particular individuals. “Lifestyle content”and/or the like refers to one or more parameters indicative of one ormore particular lifestyle aspects related to one or more particularindividuals. Example types of lifestyle content may include parametersrepresentative of an individual's diet (e.g., food, beverages,supplements, etc.), media consumption (e.g., media type, media title,media genre, etc.), medications, and/or exercise habits, routines,and/or experiences, although claimed subject matter is not limited inscope in these respects. In an embodiment, a biosphere ledger mayinclude parameters indicative environmental context for one or moreentries of a bio-ledger. For example, one or more bio-ledger entries mayindicate a change in epigenetic and/or other omic state for a particularindividual. In embodiment, one or more entries of a biosphere ledger mayindicate an environmental context in which a change in epigenetic and/orother omic state may have occurred. For example, a bio-ledger mayindicate one or more changes in epigenetic state for a particularindividual, and a biosphere ledger may include air quality measurementstaken at points in time relevant to the indicated changes in epigeneticstate. Further, for example, behavioral profile content may indicaterepeated anger states for an individual, and such states may be found torelate to particular changes in epigenetic and/or other omic states forthe individual.

In embodiments, separate databases and/or portions of databases forbio-ledger content and/or biosphere content may allow for differentsecurity and/or communication considerations and/or implementations, forexample, for the different content. Bio-ledger content and/or biosphereledger content may be stored in separate non-transitory media and/ormemory devices, for example, and/or in separate portions of anon-transitory medium and/or memory. For example, certifiedlaboratories, hospitals, doctor's offices, etc., may be permitted towrite to an individual's bio-ledger. Similarly, at-home medical devices,for example, may also be permitted to write to an individual'sbio-ledger. Further, in an embodiment, particular electronic devices,such as a bio-smart device, may be permitted to read from, but not writeto, an individual's bio-ledger, for example, at least in part to improvean electronic device's offerings with respect to a particularindividual. In some embodiments, relatively simple logging-type devices,for example, may be restricted to merely logging/writing content to anindividual's biosphere ledger, as discussed more fully below.Additionally, software services, implemented, for example, on one ormore computing devices, may log content to an individual's biosphereledger. For example, air-quality measurements and/or ultra-violet (UV)radiation level measurements for particular times and/or locations maybe obtained from publicly-available content and/or may be written to anindividual's biosphere ledger. In other embodiments, behavioral profilecontent may be written to an individual's biosphere ledger, for example.Of course, subject matter is not limited in scope in these respects. Inan embodiment, bio-ledger content and/or biosphere content may bewritten and/or recorded to a secure storage device, for example, atleast in part via wired and/or wireless network communication between acomputing device, such as a bio-smart device (discussed below) and asecure storage device.

In an embodiment, a goal of gathering and/or storing biosphere ledgercontent may include tracking histories of environmental influences towhich one or more individuals may be exposed. Example environmentalinfluencers may include, but are not limited to, exposure to monitoredenvironmental conditions (e.g., air quality, ultra-violet radiation,noise pollution, etc.), substances consumed by an individual (e.g., anindividual's diet), and/or media content consumed by an individual(e.g., watching particular television shows, reading a particular book,etc.). In an embodiment, biosphere ledger entries may be time-stamped.For example, a parameter indicative of a particular time of measurementmay be stored in a biosphere ledger in connection with a particular airquality measurement parameter. A number of measurements may be takenand/or measurement parameters stored over a period of time, for example.In an embodiment, a biosphere ledger may include entries for any numberof particular individuals and/or for one or more populations ofindividuals, for example. In an embodiment, biosphere ledger entries maybe indexed on a per-individual basis to permit retrieval of particularentries pertaining to a particular individual, for example.

In an embodiment, one or more biosphere ledger entries may include arespective metric of influence parameter. “Metric of influence” in thiscontext refers to a degree of relevance to a particular individual. Inan embodiment, a metric of influence parameter may be representative ofa measure of relevance with respect to a particular biosphere ledgerentry. Further, in an embodiment, a metric of influence parameter may bedetermined based at least in part on a distance factor, a frequencyfactor, or a relative granularity factor, or any combination thereof.For example, a distance factor may indicate a measure of proximity to aparticular sensor for an individual for a corresponding biosphere entryfor the particular individual. For example, an air quality measurementtaken by an air filter device within an individual's home may beassigned a greater relevance score with respect to a distance factorthan would an air quality measurement taken at a regional airport.

Also, for example, a frequency factor may indicate a frequency at whichparticular measurements are taken. In an embodiment, an appropriatefrequency of measurement may be dependent on the nature of themeasurement. For example, with respect to rainfall measurements, it maybe more advantageous to measure hourly rather than monthly. However,per-second measurements may not be desirable. In an embodiment, afrequency factor of a metric of influence may be assigned a value basedat least in part on how closely a rate of measurement matches a rate ofchange in the subject being measured, although subject matter is notlimited in scope in this respect. Also, in an embodiment, a relativegranularity factor may include an indication of appropriateness for aparticular measurement for a particular individual. For example, while acounty-level smog count may be a relatively good gauge of particulateconsumption for a particular individual, another individual's smarte-cigarette may be assigned a relatively higher relative granularityfactor for that particular individual due at least in part to knownconsumption of particulates from the electronic cigarette.

Further, in an embodiment, one or more biosphere ledger entries mayinclude parameters indicative of consent and/or permission. For example,because in some situations multiple sources may have access to abiosphere ledger, individual entries of a biosphere ledger may includeparameters representative of particular privacy levels that may provideconsent and/or permission to particular devices to access the biosphereentries. For example, parameters indicative of consent to accessparticular entries within a biosphere ledger may include contentidentifying one or more particular devices and/or one or more particularindividuals that have been granted permission to access the particularentries. Any devices and/or individuals attempting to access particularentries without such consent may be denied access.

Additionally, in an embodiment, one or more biosphere entries mayinclude one or more parameters indicative of a location associated withone or more environmental measurements. For example, air qualitymeasurement parameters may be stored within a biosphere ledger alongwith parameters indicating locations of measurement devices involved intaking the measurements. In an embodiment, location parameters mayinclude satellite positioning system (e.g., GPS) coordinates, althoughsubject matter is not limited in scope in this respect.

Also, in an embodiment, one or more biosphere entries may include one ormore parameters representative of a tangibility metric. In anembodiment, some devices, systems, and/or processes may contributerelatively less tangible, and/or perhaps relatively less proven,influencer content. For example, influencer factors associated withexposure to stress and/or events with potential emotional consequencesmay be assigned a tangibility metric that may indicate a reduced levelof tangibility as compared with other relatively more tangible and/orrelatively more proven influencer factors. In an embodiment, inclusionof relatively less tangible influencer factors in a biosphere ledger mayhelp to mitigate false-positive correlations in machine learning models,for example. However, embodiments may also include parametersrepresentative of a tangibility metric to identify, at least in part,biosphere entries that may be based at least in part on emotional ratherthan physical factors, subjective rather than objective factors, and/orvalues calculated via an algorithm rather than directly measured, forexample. In an embodiment, a tangibility metric associated withrespective biosphere ledger entries may allow for a relatively expandedconcept of environment and/or environmental influencers.

Returning to FIG. 2, behavioral profile content may be tracked, asdepicted at block 230. As described in more detail herein, behavioralprofile content may be derived, at least in part, from content obtainedfrom one or more sensors (e.g., microphone, camera, accelerometer,compass, etc.). For example, content obtained from one or more sensorsmay be processed by particular hardware circuitry to generate behavioralprofile content representative of a particular individual's physical,mental, and/or emotional state. In an embodiment, behavioral profilecontent may include a plurality of parameters representative of focalpoint, excitement, anger, fear, fatigue, dehydration, orfocus/distraction, or any combination thereof, in relation to aparticular individual. Behavioral profile content may further include,by way of additional non-limiting examples, parameters representative ofpre-breakthrough, silent like, regret/error acknowledgment, hunger,sloppiness/precision, empathy, and/or social engagement level, or anycombination thereof. Further, in an embodiment, as depicted at block240, epigenetic and/or other omic content and/or behavioral profilecontent may be analyzed and/or otherwise processed, such as via abehavioral processing unit, to identify relationships and/orcorrelations between particular behaviors and changes in epigeneticstate for one or more individuals. Further, embodiments may also includeomic content and/or behavioral profile content related to particularplants, such as may be advantageously utilized in agricultural settings,for example. In an embodiment, machine learning and/or other analysistechniques may be utilized to identify relationships and/or correlationsbetween particular behaviors and/or changes in epigenetic and/or otheromic state for a particular individual, although subject matter is notlimited in scope in these respects.

As depicted at block 250, a further change in epigenetic state for aparticular individual may be detected and/or predicted. In anembodiment, a further change in epigenetic state may be detected and/orpredicted based, at least in part, on identified relationships and/orcorrelations between particular behaviors and particular changes inepigenetic state and/or also based at least in part on continued trackedbehavioral profile content. In an embodiment, notification may be madeto an individual, health professional, farmer, etc., at least in part inresponse to a further detected and/or predicted change in epigeneticstate for a particular individual, as indicated at blocks 260 and/or270, for example.

FIG. 3a is a schematic block diagram depicting an embodiment 300 of anexample device, system, and/or process for communication of epigeneticcontent among various electronic devices. For example, embodiment 300may include a secure storage device, such as secure storage device 400,that may maintain and/or access a database, such as database 490, thatmay store a bio-ledger and/or a biosphere ledger associated with one ormore individuals, such as user 310. Embodiment 300 may also include abio-smart device, such as bio-smart device 900, and/or an intermediarydevice, such as intermediary device 700. In general, and as discussedmore fully below, an intermediary device, such as intermediary device700, may be utilized to enable relatively secure communication ofbio-ledger and/or biosphere ledger content between a secure storagedevice, such as secure storage device 400, and another device, such asbio-smart device 900.

In an embodiment, an intermediary device, such as intermediary device700, may be worn and/or carried, for example, by an individual, such asuser 310. As depicted in FIG. 3b , an individual, such as user 310, mayconnect an intermediary device, such as intermediary device 700, to asecure storage device and/or system, such as secure storage device 400.In an embodiment, an intermediary device, such as intermediary device700, may initiate communication of one or more parameters, such asparameter 311, particularly identifying a particular intermediarydevice, such as intermediary device 700, and/or a particular individual,such as user 310. In an embodiment, various parameters, such as securitytokens, communications parameters, and/or cryptographic keys, forexample, may be assigned to a particular individual, such as user 310,and/or to a particular intermediary device, such as intermediary device700. In an embodiment, security, communication, and/or cryptographicparameters, for example, may be utilized by electronic devices, such asbio-smart device 900 and/or intermediary device 700, to accessbio-ledger and/or biosphere ledger entries pertaining to a particularindividual, such as user 310.

In an embodiment, at least in part in response to an intermediarydevice, such as intermediary device 700, being connected to a securestorage device, such as secure storage device 400, one or more security,communication, and/or cryptographic parameters, such as parameters 313,may be transferred from a secure storage device, such as secure storagedevice 400, to an intermediary device, such as intermediary device 700.Communications, between an intermediary device, such as intermediarydevice 700, and a secure storage device, such as secure storage device400, may be accomplished via a wired connection, in an embodiment. Whilesome embodiments may provide for wireless connection, securityadvantages may be realized through the use of a wired connection, in anembodiment. For example, user 310 may physically connect intermediarydevice 700 to secure storage device 400 via an external deviceinterconnect, such as a USB port (see, for example, Universal Serial BusRevision 3.2 Specification, published Sep. 22, 2017). In an embodiment,at least in part in response to a connection, such as via a USB port, ofan intermediary device, such as intermediary device 700, at least oneprocessor of a secure storage device, such as secure storage device 400,may initiate communication of one or more security, communication,and/or cryptographic parameters, such as parameters 313, between asecure storage device, such as secure storage device 400, and anintermediary device, such as intermediary device 700. In an embodiment,one or more parameters, such as parameters 313, may include one or moretokenized security parameters, as explained more fully below. In anembodiment, a tokenized security parameter, for example, may be utilizedby an electronic device, such as a bio-smart device, to request accessto particular content from a particular individual's bio-ledger and/orbiosphere ledger, as also explained more fully below.

As depicted at FIG. 3c , an individual, such as user 310, at his or herdiscretion, for example, may physically bring an intermediary device,such as intermediary device 700, into proximity with an electronicdevice, such as bio-smart device 900, and/or may physically connect anintermediary device, such as intermediary device 700, to an electronicdevice, such as bio-smart device 900. At least in part in response to awired and/or wireless connection of intermediary device 700 to bio-smartdevice 900, for example, one or more security, communication, and/orcryptographic parameters, such as parameters 313, may be communicatedbetween intermediary device 700 and bio-smart device 900. In anembodiment, an intermediary device, such as intermediary device 700, maydetermine whether a bio-smart device, such as bio-smart device 900, hasbeen pre-certified before initiating transmission of parameters betweenthe intermediary device and the bio-smart device. For example, a securestorage device, such as secure storage device 400, may store and/orotherwise maintain a listing of bio-smart devices authorized to obtainsecurity, communication, and/or cryptographic parameters. Anintermediary device may, in an embodiment, check with a secure storagedevice, such as secure storage device 400, to determine whether abio-smart device, such as bio-smart device 900, is authorized to receivesecurity, communication, and/or cryptographic parameters. For example,an intermediary device 700 may communicate via a network, such as theInternet, with secure storage device 400, to determine whether bio-smartdevice 900 is pre-certified, for example. In an embodiment,“pre-certified” refers to a computing device, such as secure storagedevice 400, storing a certificate and/or other parameter indicative of aparticular computing device's status with respect to permissions,licenses, and/or authorizations to read from and/or to write to and/orrecord to a particular individual's bio-ledger and/or biosphere ledger.Further, in an embodiment, an individual, such as user 310, may provideapproval for communication of parameters between intermediary device 700and bio-smart device 900, for example, such as via one or more inputsprovided via a user interface of intermediary device 700 and/or ofbio-smart device 900, for example. In other embodiments, user approvalmay be inferred from a physical connection of an intermediary device,such as intermediary device 700, and a bio-smart device, such asbio-smart device 900. At least in part via communication of particularparameters, such as parameters 313, for example, an individual, such asuser 310, may grant access (e.g., read and/or write access) toparticular content, such as one or more entries of bio-ledger 492 and/orbiosphere ledger 494, to a particular electronic device, such asbio-smart device 900. Without parameters, such as parameters 313,obtained from an intermediary device, such as intermediary device 700,an electronic device, such as bio-smart device 900, may not be allowedaccess to particular content, such as bio-ledger 492 and/or biosphereledger 494, for example.

FIG. 3d depicts an example communication between a bio-smart device,such as bio-smart device 900, and a storage device, such as securestorage device 400, in accordance with an embodiment. In an embodiment,one or more communication parameters, such as one or more parameters313, may indicate a particular address on a particular network, such asthe Internet, at which a secure storage device, such as secure storagedevice 400, may be located. Utilizing, at least in part, one or moresuch communications parameters, such as parameters 313, an electronicdevice, such as bio-smart device 900, may establish communication with asecure storage device, such as secure storage device 400. In anembodiment, communication between bio-smart device and secure storagedevice 400 may include signal packet communications and/or signal framecommunications, also referred to as signal packet transmissions and/orsignal frame transmissions over a network, such as the Internet. Suchcommunications may include wired and/or wireless communication ofcontent (e.g., signals and/or states) between nodes of a network, wherea node may comprise one or more network devices and/or one or morecomputing devices, for example

Further, for example, parameters, such as parameters 313, may includeone or more security parameters, such as one or more tokenized securityparameters, that may indicate, directly and/or indirectly, an identityof a particular individual, such as user 310, and/or that may indicate,directly and/or indirectly, an identity of a particular intermediarydevice, such as intermediary device 700. In an embodiment, a securestorage device, such as secure storage device 400, may determine whethera bio-smart device, such as bio-smart device 900, is authorized (e.g.,via a pre-certification process) to access bio-ledger and/or biosphereledger content. For example, a secure storage device, such as securestorage device 400, may receive one or more such security parameters,such as one or more parameters 313, from an electronic device, such asbio-smart device 900. Secure storage device 400, for example, may permitaccess to particular entries of bio-ledger 492 and/or biosphere ledger494, as depicted at arrow 332, based at least in part on a determinationas to whether bio-smart device 900 is authorized (e.g., via apre-certification process) to access such content. In an embodiment,parameters, such as parameters 313, for example, may be communicatedbetween a bio-smart device, such as bio-smart device 900, and a securestorage device, such as secure storage device 900, at least in part byway of one or more signal packets in a wired and/or wireless connection,such as via a wired Ethernet connection and/or a wireless local areanetwork connection (WLAN), for example. Further, in an embodiment, oneor more signals packets may be communicated via a network, such as theInternet. Additionally, in an embodiment, if a bio-smart device, such asbio-smart device 900, is determined by a secure storage device, such assecure storage device 400, to not be authorized (e.g., via apre-certification process), an error message may be returned to thebio-smart device. In an embodiment, an error message may be communicatedby way of one or more signal packets via a wired and/or wiredconnection, such as via a wired Ethernet connection and/or a WLAN, forexample. As mentioned, for example, cryptographic parameters, such asone or more parameters 313, may include one or more encryption and/ordecryption keys. In an embodiment, an electronic device, such asbio-smart device 900, may decrypt content, such as bio-ledger and/orbiosphere ledger entries, for example, that may be obtained from asecure storage device, such as secure storage device 400.

Additionally, in an embodiment, a bio-smart device, such as bio-smartdevice 900, may generate and/or otherwise obtain content pertaining to aparticular individual, such as user 310. Further, generated and/orotherwise obtained content may be provided to a secure storage device,such as secure storage device 400. For example, a bio-smart device, suchas bio-smart device 900, may generate biosphere and/or bio-ledgercontent, such as content 333, pertaining to a particular individual,such as user 310. A bio-smart device, such as bio-smart device 900, mayinitiate transmission of generated and/or otherwise obtained biosphereand/or bio-ledger content, such as content 333, for example, to a securestorage device, such as secure storage device 400. Further, a bio-smartdevice, such as bio-smart device 900, may initiate communication ofgenerated and/or otherwise obtained biosphere and/or bio-ledger content,such as content 333, to an intermediary device, such as intermediarydevice 700.

In an embodiment, a secure storage device, such as secure storage device400, may operate, at least in part, as a centralized storage forepigenetic and/or other omic content, such as bio-ledger content 492and/or biosphere ledger content 494, for any number of particularindividuals. Further, in an embodiment, a secure storage device and/orsystem, such as secure storage device 400, may be located at a doctor'soffice, diagnostics lab, genetic lab, and/or other medical and/orscientific institution, to name a few non-limiting examples. At least inpart via selective dissemination of particular security, communication,and/or cryptographic parameters to particular electronic devices,content stored in a database, such as database 490, may be relativelysecurely maintained. In an embodiment, a particular individual, such asuser 310, may control communication of bio-ledger and/or biosphereledger content pertaining to that particular individual at least in partby controlling dissemination of particular security, communication,and/or cryptographic parameters.

Although example embodiments may describe a secure storage device, suchas secure storage device 400, storing bio-ledger and/or biospherecontent and also providing communication, security, and/or cryptographicparameters to electronic devices, such as intermediary device 700, otherembodiments may utilize separate devices, systems, and/or processes forstoring bio-ledger and/or biosphere content and disseminatingcommunication, security, and/or cryptographic parameters. For example,communication, security, and/or cryptographic parameters may beassigned, stored, and/or communicated at a device and/or system separatefrom secure storage device 400. Also, as mentioned herein, a securestorage device, such as secure storage device 400, may include one ormore computing devices, and/or may include a number of distributedcomputing devices. For example, embodiments may employ distributedcomputing and/or communication approaches in which portions of aprocess, such as signal processing and/or storage of signal samples, forexample, may be allocated among various devices, including one or moreclient devices and/or one or more server devices, via a computing and/orcommunications network, for example.

Further, in an embodiment, communication between a secure storagedevice, such as secure storage device 400, and an electronic device,such as bio-smart device 900, for example, may occur via a wiredconnection or via a wireless connection, or a combination thereof.Non-limiting examples of wired and/or wireless communication interfaces,networks, specifications, protocols, etc., are provided below.

FIG. 4 is an illustration of an example storage device, in accordancewith an embodiment. In an embodiment, a secure storage device, such assecure storage device 400, may access, store, and/or maintain epigeneticand/or environmental content within a database, such as database 490. Inan embodiment, a database, such as database 490, may include one or moremass storage devices and/or memory devices. Example storage deviceand/or memory device types are mentioned below. In an embodiment, adatabase, such as database 490, may include bio-ledger 492 and/orbiosphere ledger 494. As utilized herein, “secure storage” and/or“secure storage device” refer to at least one apparatus, such as atleast one computing device, including at least one non-transitory mediumand/or memory, to store content, such as bio-ledger and/or biosphereledger content, and/or to implement one or more security protocolsand/or techniques to at least partially safeguard content, such asbio-ledger content and/or biosphere ledger content, from unauthorizedaccess. For example, a secure storage device, such as secure storagedevice 400, may allow access to one or more entries of a bio-ledger,such as bio-ledger 492, and/or to one or more entries of a biosphereledger, such as biosphere ledger 494, at least in part in response to acommunication of appropriate security tokens between a device, such as abio-smart device 900, and a secure storage device, such as securestorage device 400.

In an embodiment, a secure storage device, such as secure storage device400, may include at least one processor, such as processor 410. In anembodiment, at least one processor, such as processor 410, may initiatetransmission of one or more communication, security, and/orcryptographic parameters to an electronic device, such as intermediarydevice 700. For example, processor 410 may initiate communication of oneor more communication, security, and/or cryptographic parameters to anelectronic device, such as intermediary device 700, at least in part inresponse to an electronic device, such as intermediary device 700,becoming connected to secure storage device 400. In an embodiment, asecure storage device, such as secure storage device 400, may compriseone or more communications interfaces, such as communications interface420. One or more communications interfaces, such as communicationsinterface 420, may enable wireless communications between a securestorage device, such as secure storage device 400, and one or more othercomputing devices, such as intermediary device 700 and/or bio-smartdevice 900, for example. In an embodiment, wireless communications mayoccur substantially in accordance any of a wide range of communicationprotocols, such as those mentioned herein, for example.

Also, in an embodiment, a secure storage device, such as secure storagedevice 400, may include an external device interface, such as externaldevice interface 440. In an embodiment, an external device interface,such as external device interface 440, may be substantially compatibleand/or substantially compliant with a USB specification, althoughsubject matter is not limited in scope in these respects. In anembodiment, an electronic device, such as intermediary device 700, mayconnect to and/or communicate with a secure storage device, such assecure storage device 400, via a wired connection (e.g., via externaldevice interface 440), and/or via a wireless connection (e.g., viacommunications interface 420).

In an embodiment, a secure storage device, such as secure storage device400, may further include a memory, such as memory 430. In an embodiment,memory 430 may comprise a non-volatile memory, for example. Further, inan embodiment, a memory, such as memory 430, may have stored thereinexecutable instructions, such as for one or more operating systems,communications protocols, and/or applications, for example. A memory,such as 430, may further store intermediary device parameters, such asparameters 460. In an embodiment, parameters 460 may include one or moreparticular communications, security, and/or cryptographic parametersthat may be assigned to a particular individual, such as user 310,and/or to a particular electronic device, such as intermediary device310. A secure storage device, such as secure storage device 400, mayfurther include a security tokenization unit, such as unit 470. In anembodiment, a security tokenization unit, such as unit 470, may generateone or more security tokens to at least temporarily associate aparticular individual and/or particular entries of stored content, suchas one or more entries of bio-ledger 492 and/or biosphere ledger 494,with a particular parameter, such as one or more parameters 460 and/or313, for example.

In an embodiment, processor 410 may initiate communication of parameters460 to another electronic device, such as intermediary device 700, atleast in part in response to a connection of another electronic device,such as intermediary device 700, to secure storage device 400 either viaexternal device interface 440 and/or via communications interface 420,for example. Further, in an embodiment, a secure storage device, such assecure storage device 400, may comprise a display, such as display 450,and/or may include input/output circuitry, such as circuitry 470, forexample. In an embodiment, input/output circuitry may include circuitryto accommodate a keyboard, mouse, stylus, audio speaker, microphone,printer, etc., to name but a few non-limiting examples of input and/oroutput devices.

FIG. 5 is an illustration of an embodiment 500 of an example process forinitiating communication of one or more parameters, such ascommunication, security, and/or cryptographic parameters, from a securestorage device, such as secure storage device 400, to an intermediarydevice, such as intermediary device 700. Embodiments in accordance withclaimed subject matter may include all of blocks 510-560, fewer thanblocks 510-560, and/or more than blocks 510-560. Further, the order ofblocks 510-560 is merely an example order, and subject matter is notlimited in scope in these respects. In an embodiment, an example processfor initiating communication of one or more parameters, such ascommunication, security, and/or cryptographic parameters, to anintermediary device may be implemented, at least in part, viautilization of a secure storage device, such as secure storage device400, although the scope of subject matter is not limited in scope inthis respect.

As depicted at block 510, omic and/or other epigenetic contentpertaining to one or more individuals may be obtained. In an embodiment,omic and/or epigenetic content may be obtained by a secure storagedevice, such as secure storage device 400, at least in part byreceiving, at communications interface 420, signal packets and/or signalframes, for example, transmitted over a network, such as the Internet.In an embodiment, epigenetic and/or other omic content may be obtainedat least in part by receiving signal packets and/or signal frames fromtest lab computing devices, doctor office computing devices, etc. In anembodiment, omic and/or other epigenetic content may be stored as one ormore bio-ledger entries and/or one or more biosphere entries, asdepicted at block 520, for example. In an embodiment, bio-ledger entriesand/or biosphere entries may be stored, for example, as signals and/orstates in one or more non-transitory media and/or memories and/or massstorage devices of a secure storage device, such as secure storagedevice 400. As mentioned, bio-ledger entries may include parametersrepresentative of one or more aspects of genetic content, epigeneticcontent, microbiome content, proteome content, metabolome content, ortranscriptome content, or any combination thereof, associated withand/or pertaining to one or more particular individuals, for example.Bio-ledger entries may further include lab test content for one or moreparticular individuals, content representative of diagnosed diseases forone or more particular individuals, identified risk factors for one ormore particular individuals, etc., although subject matter is notlimited in scope in this respect. Further, as mentioned, biosphereledger entries may include parameters representative of one or moreenvironmental aspects related to one or more particular individuals, forexample.

In an embodiment, an intermediary device may be detected, as indicatedat block 530. For example, a secure storage device, such as securestorage device 400, may detect a physical and/or electrical connectionof an intermediary device, such as intermediary device 700, to anexternal device interface, such as external device interface 440. Foranother example, a secure storage device, such as secure storage device400, may detect a wireless connection of an intermediary device, such asintermediary device 700, via a communications interface, such ascommunications interface 420. In some embodiments, security advantagesmay be experienced through an implementation of a wired connectionbetween secure storage device 400 and intermediary device 700. Forexample, intermediary device 700 may connect to secure storage device400 by way of a USB interface and/or another type of wired interface.Further, in an embodiment, at least in part in response to detection ofan intermediary device, such as intermediary device 700, a device, suchas secure storage device 400, may transmit one or more communicationparameters to an intermediary device, such as intermediary device 700,as indicated at block 540. Additionally, at least in part in response todetection of an intermediary device, such as intermediary device 700, adevice, such as secure storage device 400, may transmit one or moresecurity parameters to an intermediary device, such as intermediarydevice 700, as indicated at block 550. Further, in an embodiment, atleast in part in response to detection of an intermediary device, suchas intermediary device 700, a device, such as secure storage device 400,may transmit one or more cryptographic parameters (e.g., encryptionand/or decryption keys) to an intermediary device, such as intermediarydevice 700, as indicated at block 560. In an embodiment, parameters,such as one or more security parameters, communication parameters,and/or cryptographic parameters, may be transmitted from a securestorage device, such as secure storage device 400, to an intermediarydevice, such as intermediary device 700, as one or more signals and/orsignals packets via a wired interconnect, such as via a USBinterconnect, for example. For example, external device interface 440may comprise a USB hub device, and communication between secure storagedevice 400 and intermediary device 700 may include USB signal packettransmissions performed under control on external device interface 440,for example. As mentioned above and as further discussed below, anintermediary device, such as intermediary device 700, may be utilized torelatively securely communicate parameters, such as one or more securityparameters, communication parameters, and/or cryptographic parameters,between a secure storage device, such as secure storage device 400, andanother device, such as bio-smart device 900. In an embodiment,parameters, such as one or more security parameters, communicationparameters, and/or cryptographic parameters, may allow a device, such asbio-smart device 900, to request access to content, such as particularbio-ledger and/or biosphere ledger content pertaining to a particularindividual, from a secure storage device, such as secure storage device400.

FIG. 6 is an illustration of an embodiment 600 of an example process forinitiating communication of epigenetic content parameters, in accordancewith an embodiment. Embodiments in accordance with claimed subjectmatter may include all of blocks 610-650, fewer than blocks 610-650,and/or more than blocks 610-650. Further, the order of blocks 610-650 ismerely an example order, and subject matter is not limited in scope inthese respects. In an embodiment, an example process for initiatingcommunication of omic and/or other epigenetic content parameters may beimplemented, at least in part, via utilization of a secure storagedevice, such as secure storage device 400, although the scope of subjectmatter is not limited in scope in this respect.

In an embodiment, an electronic device, such as secure storage device400, may monitor for requests from one or more bio-smart devices, suchas bio-smart device 900, as indicated at block 610. In an embodiment, arequest from a bio-smart device, such as bio-smart device 900, may bereceived as one or more signals and/or states via a wireless and/orwired network interface, such as communications interface 420, forexample. For example, bio-smart device 900 may transmit a request tocommunicate with secure storage device 400 via one or more signalpackets over a wired and/or wireless connection. Example wired and/orwireless interconnect technologies are mentioned below, although claimedsubject matter is not limited in scope in these respects. In anembodiment, bio-smart device 900 may transmit a request to communicatewith secure storage device 400 via one or more signal packets over awired Ethernet connection and/or via a WLAN connection, for example. Inan embodiment, bio-smart device 900 may communicate with secure storagedevice 400 via a network, such as the Internet. Further, in anembodiment, a request from a bio-smart device, such as bio-smart device900, may include one or more parameters, such as one or more securityparameters. In an embodiment, a security parameter, such as may beprovided to a bio-smart device by an intermediary device, such asintermediary device 700, may indicate, for example, a particularindividual and/or may identify a particular intermediary device. Asmentioned, an intermediary device, such as intermediary device 700, maybe utilized to relatively securely communicate parameters, such as oneor more security parameters, communication parameters, and/orcryptographic parameters, between a secure storage device, such assecure storage device 400, and another device, such as bio-smart device900. In an embodiment, parameters, such as one or more securityparameters, communication parameters, and/or cryptographic parameters,may allow a device, such as bio-smart device 900, to request access tocontent, such as particular bio-ledger and/or biosphere ledger contentpertaining to a particular individual, from a secure storage device,such as secure storage device 400.

As indicated at blocks 620 and/or 630, at least in part in response to adetection of a request from a bio-smart device, such as bio-smart device900, a processor, such as processor 410, may determine whether anappropriate security parameter has been provided by the bio-smartdevice. In an embodiment, for example, a comparison may be madeutilizing a processor, such as processor 410, to determine whether asecurity parameter provided by a bio-smart device, such as bio-smartdevice 900, matches a security parameter previously expected for aparticular individual, such as user 310, and/or to a particular userdevice, such as intermediary device 700, for example. Alternatively, inan embodiment, a secure storage device, such as secure storage device400, may determine whether bio-smart device 900 has been pre-certifiedto access the requested content. As depicted at block 640, at least inpart in response to a determination that no appropriate securityparameter was provided by a bio-smart device, such as bio-smart device900 (e.g., bio-smart device 900 is determined to not be pre-certified),at least one processor, such as processor 410, of a secure storagedevice, such as secure storage device 400, may initiate communication ofan error message to a bio-smart device, such as bio-smart device 900. Inan embodiment, an error message may be generated by a communicationsinterface, such as communications interface 420, as one or more signalsand/or signal packets for example.

Further, as depicted at block 650, at least in part in response to adetermination that an appropriate security parameter has been providedby a bio-smart device, such as bio-smart device 900 (e.g., by comparinga security token with a certificate and/or other parameter maintained bysecure storage device 400), at least one processor, such as processor410, of a secure storage device, such as secure storage device 400, mayinitiate communication of requested bio-ledger and/or biosphere ledgercontent, such as one or more requested entries from bio-ledger 492and/or biosphere ledger 494, to a bio-smart device, such as bio-smartdevice 900. In an embodiment, bio-ledger content and/or biosphere ledgercontent may be transmitted by a communication interface, such ascommunication interface 420, at least in part by generating one or moresignals and/or signal packets for transfer via a wired and/or wirelessconnection, examples of which are found below. In this manner, abio-smart device, such as bio-smart device 900, may obtain particularbio-ledger and/or biosphere ledger content pertaining to a particularindividual from a secure storage device, such as secure storage device400. Similarly, in an embodiment, a bio-smart device, such as bio-smartdevice 900, may be permitted, if determined by secure storage device 400to be authorized, to write and/or record entries to a particularindividual's bio-ledger and/or biosphere ledger entries stored at securestorage device 400. Further, in this manner, a secure storage device,such as secure storage device 400, may deny read and/or writeopportunities to particular bio-ledger and/or biosphere content toparticular devices, such as particular bio-smart devices, that provideinappropriate and/or insufficient security parameters. As mentioned, abio-smart device, such as bio-smart device 900, may obtain such securityparameters from via an intermediary device, such as intermediary device700. Utilization of an intermediary device, such as intermediary device700, to communicate security parameters allows for an individual, suchas user 310, to determine which bio-smart devices, for example, haveaccess to confidential and/or personal bio-ledger and/or biosphereledger content.

FIG. 7 is an illustration of an embodiment 700 of an exampleintermediary device. As utilized herein, “intermediary device” and/orthe like refers to an electronic device to facilitate, at least in part,communication of particular parameters between a storage device, such assecure storage device 400, and another electronic device, such asbio-smart device 900, at least in part via storage of particular signalsand/or states associated with a particular individual. In embodiments,an intermediary device, such as intermediary device 700, may beimplemented as any of a variety of device types. In embodiments,intermediary device types may include wearable and/or portableelectronic devices. For example, and not by way of limitation, anintermediary device types may include cellular phones, tablet devices,notebook computing devices, electronic watches, personal displaydevices, personal digital assistants, key fobs, portable storage devices(e.g., USB non-volatile storage stick), personal fitness devices, etc.In other embodiments, an intermediary device, such as intermediarydevice 700, may be incorporated into one or more vehicles (e.g., car,bicycle, motorcycle, etc.). Further, in embodiments, intermediarydevices, such as intermediary device 700, may be incorporated intoarticles of clothing, purses, wallets, shoes, other accessories, etc. Ofcourse, subject matter is not limited in scope in these respects.

In an embodiment, an intermediary device, such as intermediary device700, may comprise one or more processors, such as processor 710, and/ormay comprise one or more communications interfaces, such ascommunications interfaces 720 and/or 740. In an embodiment, one or morecommunications interfaces, such as communications interface 720, mayenable, at least in part, wireless communications between anintermediary device, such as intermediary device 700, and one or moreother electronic devices, such as secure storage device 400 and/orbio-smart device 900, for example. Further, in an embodiment, one ormore communications interfaces, such as communications interface 740,may enable wired communications, at least in part, between anintermediary device, such as intermediary device 700, and one or moreother electronic devices, such as secure storage device 400 and/orbio-smart device 900, for example. In an embodiment, wired and/orwireless communications may occur substantially in accordance any of awide range of communication protocols, such as those mentioned herein,for example. For example, intermediary device 700 may communicate withsecure storage device 400 by way of a wired USB connection. In anembodiment, external device interface 440 of secure storage device 400may transmit one or more signal packets to intermediary device 700 byway of a USB interconnect, for example. Similarly, communication betweenintermediary device 700 and bio-smart device 900 may include wiredcommunication, such as via a USB interconnect, and/or wirelesscommunication, such as via WLAN and/or Bluetooth, for example.

In an embodiment, an intermediary device, such as intermediary device700, may include a memory, such as memory 730. In an embodiment, memory730 may comprise a non-volatile memory, for example. Further, in anembodiment, a memory, such as memory 730, may have stored thereinexecutable instructions, such as for one or more operating systems,communications protocols, applications, etc., for example. Further, inan embodiment, an intermediary device, such as intermediary device 700,may comprise a display, such as display 750, one or more sensors, suchas one or more sensors 760. In an embodiment, sensors may include, toname a few non-limiting examples, one or more radio frequencysensors/transceivers, cameras, microphones, accelerometers, altimeters,gyroscopes, compasses, thermometers, magnetometers, barometers, lightsensors, or proximity sensors, or any combination thereof. Of course,these are merely example types of components that may be included in amobile device, and subject matter is not limited in scope to theseparticular examples.

In an embodiment, a memory, such as memory 730, of an intermediarydevice, such as intermediary device 700, may store varied types ofdigital content. For example, an intermediary device, such asintermediary device 700, may store one or more parameters obtained, forexample, from a secure storage device, such as secure storage device400. In an embodiment, an intermediary device, such as intermediarydevice 700, may store communications parameters, such as communicationsparameters 733, security parameters, such as security parameters 732,and/or cryptographic parameters, such as encryption and/or decryptionparameters 731.

As mentioned, an intermediary device, such as intermediary device 700,may obtain parameters, such as one or more security, communications,and/or cryptographic parameters, from a secure storage device, such assecure storage device 400. For example, an intermediary device, such asintermediary device 700, may obtain encryption and/or decryptionparameters 731, security parameters 732, and/or communicationsparameters 733, or any combination thereof, from a computing device,such as secure storage device 400. Further, in an embodiment, anintermediary device, such as intermediary device 700, may be utilized byan individual, such as user 310, to enable a bio-smart device, such asbio-smart device 900, to obtain parameters, such as encryption and/ordecryption parameters 731, security parameters 732, and/orcommunications parameters 733, or any combination thereof, from anintermediary device, such as intermediary device 700.

For example, an individual may physically bring an intermediary device,such as intermediary device 700, into proximity with an electronicdevice, such as bio-smart device 900, and/or may physically connect anintermediary device, such as intermediary device 700, to an electronicdevice, such as bio-smart device 900. At least in part in response to awired and/or wireless connection of intermediary device 700 to bio-smartdevice 900, for example, one or more security parameters 732,communication parameters 733, and/or encryption and/or decryptionparameters 731, may be communicated between intermediary device 700 andbio-smart device 900. Further, as mentioned, a bio-smart device, such asbio-smart device 900, may utilize one or more communication, security,and/or cryptographic parameters obtained from an intermediary device,such as intermediary device 700, to obtain epigenetic content, such asone or more bio-ledger and/or biosphere ledger entries, for a particularindividual, such as user 310, from a secure storage device, such assecure storage device 400.

In some embodiments, bio-smart devices may not be networked, andtherefore may not have a capability of communicating with a storagedevice, such as secure storage device 400, to obtain and/or tocontribute bio-ledger and/or biosphere ledger content for a particularindividual. In some embodiments, an intermediary device, such asintermediary device 700, may further store actionable biological content(e.g., epigenetic and/or other omic content that may spur action in anindividual and/or bio-smart device) related to a particular individual,such as user 310. For example, an intermediary device, such asintermediary device 700, may store particular genetic, epigeneticcontent, content related to health goals, content representative ofdoctor directive, etc., to name a few example content types. In anembodiment, an intermediary device, such as intermediary device 700, maystore bio-ledger content, such as bio-ledger content 734, and/or maystore biosphere ledger content, such as biosphere ledger content 735,for example.

In an embodiment, an intermediary device, such as intermediary device700, may obtain actionable biological content, such as particularbio-ledger entries, particular biosphere ledger entries, and/or othercontent types from a secure storage device, such as secure storagedevice 400. Further, in an embodiment, a non-networked bio-smart device,for example, may obtain actionable biological content, particularbio-ledger entries, particular biosphere ledger entries, and/or othercontent types, for example, from an intermediary device, such asintermediary device 700. In this manner, an intermediary device, such asintermediary device 700, may support and/or enable non-networkedbio-smart devices, in an embodiment.

Additionally, in an embodiment, an intermediary device, such asintermediary device 700, may store parameters, such as logged entries736, obtained from one or more electronic devices, such as one or morebio-smart devices 900. In an embodiment, a bio-smart device, such asbio-smart device 900, may initiate communication of content, such asparticular bio-ledger and/or biosphere ledger entries, to anintermediary device, such as intermediary device 700. At a subsequentpoint in time, an intermediary device, such as intermediary device 700,may upload stored content, such as logged entries 736, to a securestorage device, such as secure storage device 400, for example. In anembodiment, content, such as logged entries 736, gathered at least inpart via an intermediary device, such as intermediary device 700, may beuploaded to a bio-ledger, such as bio-ledger 492, and/or a biosphereledger, such as biosphere ledger 494, of a database, such as database490. In an embodiment, content, such as logged entries 736, gathered atleast in part via use of an intermediary device, such as intermediarydevice 700, may be analyzed and/or otherwise processed at least in partby one or more electronic devices, such as secure storage device 400,and/or may be analyzed, for example, by one or more medicalprofessionals.

Further, content, such as one or more of logged entries 736, may includesensitive, personal, and/or confidential content that may beadvantageously communicated to an individual, such as user 310, by amedical professional. For example, by having a medical professionalcommunicate sensitive, personal, and/or confidential content, such asone or more of logged entries 736, a situation may be avoided wherein adevice, such as bio-smart device 900, could be seen as offering medicaladvice. Of course, these are merely examples of how content, such aslogged entries 736, may be analyzed and/or otherwise processed. Asmentioned, at least in part because an individual, such as user 310, maymaintain possession and/or control of an intermediary device, such asintermediary device 700, an individual, such as user 310, may, at leastin part, control access to particular content, such as one or moreentries of bio-ledger 492, biosphere ledger 494, and/or logged entries736, for example.

FIG. 8 is an illustration of an embodiment 800 of an example process forinitiating communication of parameters to a bio-smart device, such asbio-smart device 900. Embodiments in accordance with claimed subjectmatter may include all of blocks 810-880, fewer than blocks 810-880,and/or more than blocks 810-880. Further, the order of blocks 810-880 ismerely an example order, and subject matter is not limited in scope inthese respects. In an embodiment, an example process for initiatingcommunication of one or more parameters, such as communication,security, and/or cryptographic parameters, to an electronic device, suchas a bio-smart device (e.g., bio-smart device 900), may be implemented,at least in part, via utilization of an intermediary device, such asintermediary device 700, although the scope of subject matter is notlimited in scope in this respect.

As depicted at block 810, an apparatus, such as intermediary device 700,may obtain one or more communication parameters from a storage device,such as secure storage device 400. For example, as mentioned,intermediary device 700 may receive signal packets and/or signal framesvia a USB interconnect from external device interface 440 of securestorage device 400. Additionally, as depicted at block 820, anapparatus, such as intermediary device 700, may obtain one or moresecurity parameters from a storage device, such as secure storage device400. Further, as depicted at block 830, an apparatus, such asintermediary device 700, may obtain one or more cryptographic parametersfrom a storage device, such as secure storage device 400. Examples ofcommunication, security, and/or cryptographic parameters are mentionedabove. Further, as mentioned, communication, security, and/orcryptographic parameters may be transferred from external deviceinterface 440 of secure storage device 400 to a wired communicationsinterface 740 of intermediary device 700 at least in part in response tointermediary device 700 becoming physically and/or electricallyconnected to secure storage device 400 via an external device interface,such as a USB connection.

In an embodiment, an apparatus, such as intermediary device 700, maymonitor for proximity and/or connection to a bio-smart device, such asbio-smart device 900, as indicated at block 840. For example, anintermediary device, such as intermediary device 700, may detect aphysical and/or electrical connection of an intermediary device, such asintermediary device 700, to an communication interface, suchcommunication interface 920, of a bio-smart device, such as bio-smartdevice 900. For another example, an apparatus, such as intermediarydevice 700, may detect a wireless signal transmitted by a bio-smartdevice, such as bio-smart device 900. For example, a wirelesscommunication interface 720 of intermediary device 700 may receive oneor more wireless, radio-frequency signals from communication interface920 of bio-smart device 900. In an embodiment, an apparatus, such asintermediary device 700, may connect via a wireless connection to abio-smart device, such as bio-smart device 900.

Further, in an embodiment, at least in part in response to detection ofa user approval of a wired and/or wireless connection between anapparatus, such as intermediary device 700, and a bio-smart device, suchas bio-smart device 900, an apparatus, such as intermediary device 700,may initiate communication of one or more communication parameters to abio-smart device, such as bio-smart device 900, as indicated at blocks850 and/or 860. In an embodiment, a wireless communication interface 720and/or wired communication interface 740 may transmit signal packetsand/or signal frames, for example, to communication interface 920, forexample. Additionally, an apparatus, such as intermediary device 700,may initiate communication of one or more security parameters to abio-smart device, such as bio-smart device 900, as indicated at block870. Wireless communication interface 720 and/or wired communicationinterface 740 may transmit signal packets and/or signal framescomprising one or more security parameters, for example, tocommunication interface 920. Further, as indicated at block 880, anapparatus, such as intermediary device 700, may initiate communicationof one or more cryptographic parameters to a bio-smart device, such asbio-smart device 900. Wireless communication interface 720 and/or wiredcommunication interface 740 may transmit signal packets and/or signalframes comprising one or more cryptographic parameters, for example, tocommunication interface 920, in an embodiment.

In an embodiment, “user approval” may be inferred from an individual,such as user 310, physically connecting an intermediary device, such asintermediary device 700, to a particular bio-smart device, such asbio-smart device 900. In other embodiments, user approval may include anindividual explicitly indicating through a user interface located on anintermediary device, such as intermediary device 700, and/or on abio-smart device, such as bio-smart device 900. For example, anindividual may interact with a fingerprint scanner and/or some otherbio-authentication device to confirm identity and/or to explicitlyapprove communication between an intermediary device, such asintermediary device 700, and a bio-smart device, such as bio-smartdevice 900. Additionally, in embodiments, an individual, such as user310, may provide prior approval to connections with one or moreparticular bio-smart devices. For example, one or more securityparameters, such as security parameters 732, may identify, at least inpart, one or more particular bio-smart devices, such as bio-smart device900, with which an intermediary device, such as intermediary device 700,may interact without obtaining additional approvals from an individual,such as user 310.

FIG. 9 is an illustration of an embodiment 900 of an example bio-smartdevice. In an embodiment, a bio-smart device, such as bio-smart device900, may analyze and/or otherwise process epigenetic content, such asone or more entries obtained from bio-ledger 492 and/or biosphere ledger494, and/or behavioral profile content, such as may be derived from oneor more sensors, for example, to help manage and/or improve abiological, behavioral, and/or emotional state of an individual, such asuser 310. For example, and as described in more detail below, abio-smart device, such as bio-smart device 900, may, in an embodiment,generate one or more recommendations directed to improvement of acurrent and/or future epigenetic state of an individual, such asparticular user 310, based at least in part on entries obtained frombio-ledger 492 and/or biosphere ledger 494 and/or based at least in parton behavioral profile content, such as may be generated, at least inpart, by a behavioral processing unit (BPU), such as BPU 1200, forexample.

For example, in an embodiment, a bio-smart device, such as bio-smartdevice 900, may include at least one processor, such as processor 910.Further, in an embodiment, a bio-smart device, such as bio-smart device900, may obtain signals and/or states representative of epigeneticcontent, such as one or more entries from bio-ledger 492 and/or one ormore entries from biosphere ledger 494, from a networked device, such assecure storage 400, via a wired and/or wireless network connectionutilizing, at least in part, a communications interface, such ascommunications interface 920. In an embodiment, wireless and/or wiredcommunications may occur substantially in accordance any of a wide rangeof communication protocols, such as those mentioned herein, for example.In other embodiments, a bio-smart device, such as bio-smart device 900,may not be networked. In embodiments utilizing non-networked bio-smartdevices, epigenetic content, such as one or more entries from bio-ledger492 and/or one or more entries from biosphere ledger 494, may beobtained from an intermediary device, such as intermediary device 700,as explained more fully below.

In an embodiment, a bio-smart device, such as bio-smart device 900, mayinclude a memory, such as memory 930. In an embodiment, memory 930 maycomprise a non-volatile memory, for example. Further, in an embodiment,a memory, such as memory 930, may have stored therein executableinstructions, such as for one or more operating systems, communicationsprotocols, and/or applications, for example. A memory, such as memory930, may further store particular instructions, such as BPU code 936,executable by a behavioral processing unit, such as 1200, to generate,at least in part, behavioral profile content. A memory, such as memory930, may also store particular instructions, such as machine learning(ML) code 938, executable at least in part by a machine-learning device,system, and/or process 940 and/or at least in part by a processor, suchas processor 910 and/or BPU 1200, for example. Additionally, in anembodiment, a memory, such as memory 930, may store one or more entriesof biosphere ledger content, such as biosphere ledger content 932,and/or one or more entries of bio-ledger content, such as bio-ledgercontent 934. For example, one or more entries of biosphere ledgercontent, such as biosphere ledger content 932, and/or one or moreentries of bio-ledger content, such as bio-ledger content 934, may beobtained from a secure storage device, such as secure storage device400, and/or may be generated by a bio-smart device, such as bio-smartdevice 900. In an embodiment, for a situation in which bio-ledger and/orbiosphere ledger content is generated by a bio-smart device, such asbio-smart device 900, bio-ledger and/or biosphere ledger content may betransmitted, such as via communications interface 920, to a securestorage device, such as secure storage device 400, for storage in aparticular individual's bio-ledger and/or biosphere ledger. In otherembodiments, bio-ledger and/or biosphere ledger content, such as one ormore entries of biosphere ledger content 932 and/or one or more entriesof bio-ledger content 934, may be transferred from bio-smart device 900to an intermediary device, such as intermediary device 700.

Although BPU 1200 and/or ML 940 is described as executing instructions,such as BPU code 936 and/or ML code 938, other embodiments of BPUsand/or ML units may not fetch and execute code. In an embodiment, a BPUmay include dedicated and/or specialized circuitry for processing sensorcontent and/or for generating behavioral profile content, as describedmore fully below. Further, an ML unit may include dedicated and/orspecialized circuitry for processing epigenetic content, sensor content,and/or behavioral profile content, for example.

Further, in an embodiment, a bio-smart device, such as bio-smart device900, may include a display, such as display 960, and/or may also includeone or more sensors, such as one or more sensors 950. As utilizedherein, “sensors” and/or the like refer to a device and/or componentthat may respond to physical stimulus, such as, for example, heat,light, sound pressure, magnetism, particular motions, etc., and/or thatmay generate one or more signals and/or states in response to physicalstimulus. Example sensors may include, but are not limited to, one ormore cameras, microphones, accelerometers, altimeters, gyroscopes,compasses, thermometers, magnetometers, barometers, light sensors,proximity sensors, hear-rate monitors, perspiration sensors, hydrationsensors, breath sensors, etc., and/or any combination thereof. In anembodiment, one or more sensors may monitor one or more aspects of aparticular operator's biological and/or behavioral state. Further, in anembodiment, one or more sensors may monitor one or more environmentalaspects.

In an embodiment, to generate behavioral profile content for aparticular individual, such as user 310, a computing device, such asbio-smart device 900, may obtain signals and/or states representative ofcontent from one or more sensors, such as one or more of sensors 950.Also, in an embodiment, a processor, such as BPU 1200, may processsensor content, such as content from one or more of sensors 150, togenerate behavioral profile content for a particular individual. In anembodiment, a processor, such as BPU 1200, may include behavioralcontent processing circuitry. For example, a processor, such as BPU1200, may include machine learning acceleration circuitry and/or mayoperate in conjunction with machine learning circuitry, such as ML unit940, in an embodiment. BPU 1200 and/or ML unit 940 may also be utilized,at least in part, to process genetic and/or epigenetic content, such asbio-ledger content 934 and/or biosphere ledger content 932, such as, forexample, to identify one or more relationships and/or correlationsbetween particular bio-ledger/biosphere content, such as bio-ledgercontent 934 and/or biosphere ledger content 932, and particularbehavioral profile content that may be gleaned, at least in part, fromsignals and/or states obtained from one or more sensors, such as sensors950. BPU 1200 and/or ML unit 940 may also be utilized, at least in part,to detect and/or predict changes in an epigenetic state of a particularindividual, such as user 310, and/or to generate one or morerecommendations directed to improvement of a current and/or futureepigenetic state of an individual, such as particular user 310.

For example, a processor, such as BPU 1200 and/or ML 940, may includeone or more arithmetic units directed to operations involving relativelylarger parameter sets, such as parameter sets that may be employed inmachine learning, such as neural networks. In an embodiment, ageneral-purpose processor, such as processor 910, and/or anotherprocessor, such as BPU 1200 and/or ML 940, may comprise separateintegrated circuit devices. In other embodiments, a general-purposeprocessor, such as processor 910, and another processor, such as BPU1200 and/or ML 940, may be formed on the same integrated circuit dieand/or integrated circuit package. Further, in an embodiment, aprocessor, such as BPU 1200 and/or ML 940, may comprise one or moreco-processors that may operate in cooperation with a general-purposeprocessor, such as 910.

In an embodiment, behavioral profile content, such as may be generatedby a BPU, such as BPU 1200, may be communicated between a BPU, such asBPU 1200, and any of a wide range of devices, systems, and/or processes.For example, behavioral profile content generated by BPU 1200 may bestored in a memory, such as memory 930, and/or may be pushed and/orotherwise made available to processor 910, to ML 940, and/or to otherdevices and/or systems. In an embodiment, behavioral profile content maybe communicated via one or more wired and/or wireless communicationnetworks between a computing device, such as bio-smart device 900, andone or more other devices, such as secure storage device 400 and/orintermediary device 700. Of course, subject matter is not limited inscope in these respects.

In an embodiment, behavioral profile content may include a particularspecified set of parameters representative of a particular individual'sbehavioral and/or biological state that may be utilized, at least inpart, by any of a wide range of devices, systems, and/or processes forany of a wide range of applications and/or purposes. In an embodiment,by generating a specified set of parameters comprising behavioralprofile content, other devices, systems, applications, and/or processes,for example, may be relieved of responsibility for generating behavioralprofile content and may, instead, concentrate on particular areas ofexpertise and/or specialization. For example, application developers maydesign applications to take advantage of one or more parameters ofbehavioral profile content for one or more particular operators withouthaving to incur the costs (time, money, resources, etc.) of developingcircuitry, code, etc. for gathering and/or processing sensor contentand/or for generating behavioral profile content. In an embodiment, abio-smart device, such as bio-smart device 900, may utilize behavioralprofile content at least in part to identify one or more relationshipsand/or correlations between particular bio-ledger/biosphere content,such as bio-ledger content 934 and/or biosphere ledger content 932, andparticular behavioral profile content. Behavioral profile content mayalso be utilized, at least in part, by a bio-smart device, such asbio-smart device 900, to detect and/or predict changes in an epigeneticstate of a particular individual, such as user 310, and/or to generateone or more recommendations directed to improvement of a current and/orfuture epigenetic state of an individual, such as particular user 310.

In general, bio-smart devices, such as bio-smart device 900, maycomprise a relatively “intelligent” bio-smart device. In an embodiment,a bio-smart device may advantageously process and/or otherwise analyzebehavioral profile content generated by the bio-smart device with omiccontent, such as content from a particular individual's bio-ledgerand/or biosphere ledger entries, to improve operation and/or outputgenerated by the device and/or to improve resource allocation within thedevice.

Other embodiments may include a “logging” type device. In an embodiment,a logging-type device may log particular content to one or moreparticular individual's biosphere ledger and/or bio-ledger. For example,a logging-type device, such as logging-type device 1500 depicted in FIG.15a and as discussed below, may include a sensor, such as an air qualitysensor, and/or may log measurements to a memory store, wherein thememory store includes one or more biosphere ledger entries and/or one ormore bio-ledger entries for one or more particular individuals. Asdiscussed more fully below, such logging-type devices may, in anembodiment, be employed across a geographical area and/or may help trackparticular environmental conditions across a population of individuals,for example. In an embodiment, a logging-device intended to logbiosphere and/or bio-ledger entries for a particular individual maycomprise a “personal” and/or “private” logging device. In an embodiment,biosphere and/or bio-ledger entries logged by personal logging devicesmay not generally be shared. On the other hand, for example, a “public”logging device may log biosphere ledger and/or bio-ledger entriesintended to be shared among a number of individuals and/or across apopulation of individuals. Example logging-type devices are discussedmore fully, below.

In further embodiments, a bio-smart device may comprise an industrialscale-type bio-smart device. For example, some devices may be tooexpensive for individuals, in many case, to individually purchase.Industrial-scale type bio-smart devices may process epigenetic and/orbehavioral profile content related to multiple particular individuals,and/or may access/write to bio-ledgers and/or biosphere ledgerspertaining to multiple particular individuals. In an embodiment, somelogging-type bio-smart devices may also comprise industrial scale-typedevices. For example, one or more air quality type of bio-smart devicesmay be utilized by a number of individuals across a geographical area,as mentioned above. Ownership of a number of air quality sensors wouldbe prohibitive for many individuals. Thus, embodiments that allow formultiple individuals to take advantage of one or more shared bio-smartdevices may be desirable. Similarly, bio-smart gymnasium equipment maycomprise industrial scale-type and/or intelligent-type bio-smartdevices. Other examples of bio-smart devices and/or device types areprovided below.

In other embodiments, a particular individual's bio-smart device mayoperate in conjunction with public devices to write and/or recordappropriate content to an individual's biosphere ledger. For example, abio-smart home water faucet may communicate, such as via a networkconnection, with a bio-smart water testing device employed at aneighborhood level (e.g., testing device located in water pipe serving aparticular neighborhood). A bio-smart faucet may measure a quantity ofwater flowing into an individual's home and a neighborhood-levelbio-smart water testing device may measure water quality and/orparticulates. Content generated by both bio-smart devices may beutilized to generate content for one or more individual's biosphereledgers, in an embodiment. In this manner, a more detailed and/or morecomprehensive picture of water purity and/or safety may be established,thereby helping to improve the wellbeing of a number of people.

For another example, a bio-smart refrigerator device may detect a numberof containers of a particular product to have been consumed by one ormore particular individuals. Bio-smart devices may be located, forexample, at a manufacturer of a particular food product. A bio-smartdevice may, for example, measure aspects related to the food product,and content obtained from the bio-smart device located at the foodproduct manufacturer may be written to and/or recorded in a particularindividual's biosphere ledger. Further, for example, a bio-smartrefrigerator may detect and/or record an amount of the particular foodproduct removed from the refrigerator by the particular individual. Thebio-smart refrigerator may write and/or record the amount of theparticular food product to the particular individual's biosphere ledger,in an embodiment. By maintain a ledger, such as a biosphere ledger,containing details related to the particular food product and the amountremoved from the refrigerator, for example, a bio-smart device, such asa bio-smart refrigerator, may detect patterns between particularconsumed foods and particular changes in epigenetic and/or other omicstate for the particular individual, and/or may make recommendations tothe individual with respect to dietary intake with the goal of improvingthe epigenetic and/or other omic state of the individual. In short, abio-smart device, such as an example bio-smart refrigerator, may helpimprove the health and/or wellbeing of the individual in ways thatconventional refrigerators and/or other devices are not able. Further,coordination of multiple bio-smart type devices may provideopportunities for third-party services to connect content fromindustrial-type devices with private-device content to generaterelatively more comprehensive biosphere ledger entries.

Examples of other types of bio-smart devices that may utilize biologicalcontent, sensor content, and/or machine learning, for example, mayinclude, for example, an epigenetics-aware smart scale. For example, abio-smart weight scale, such as may be designated for human use, mayidentify pre-diabetic conditions. In an embodiment, a bio-smart weightscale may monitor weight changes and/or may notify an individual atleast in part in response to weight changes and/or at least in part dueto changes in bio-ledger content (e.g., epigenetic and/or other omiccontent) indicating a risk of being permanent and/or affecting futureoffspring at various points in time. In another embodiment, anepigenetics-aware air quality monitor may identify specific sensitivesbased at least in part on air pollutants and/or epigenetic changes.Further, in an embodiment, an epigenetics-aware breathalyzer/gas sensormay relate epigenetic changes to levels of tobacco, alcohol, and/orother detected chemical compounds. Additionally, in an embodiment, anepigenetics-aware refrigerator may relate epigenetic changes to dietarychanges, for example. In another embodiment, an epigenetics-aware alarmclock and/or sleep tracker may warn an individual of damaging changesfrom repeated sleep patterns. Of course, subject matter is not limitedin scope in these respects. In general, embodiments of bio-smartdevices, such as bio-smart device 900, may provide improved offerings ascompared with non-bio smart counterparts. For example, a conventionalscale is not going to be able to indicate when a weight change mightaffect the health of future offspring and/or indicate when new dietaryhabits may have adverse and/or positive effects on an individual'shealth, such as measured by epigenetic and/or other omic changes.

In an embodiment, bio-smart devices may operate with limited computingresources, for example. In an embodiment, it may be advantageous tomanage resource allocation to help ensure a device, such as bio-smartdevice 900, operates within specified storage, computational, and/orenergy budgets, and/or to maintain competitive pricing. In anembodiment, bio-ledger content may provide a guide for improved resourceallocation techniques and/or for improved content compressiontechniques. For example, improved content compression techniques maymaintain content more relevant to a specified task based, at least inpart, on particular bio-ledger content, for example.

In an embodiment, a bio-smart mirror, for example, may utilizeepigenetic and/or genetic content to identify, at least in part, mentalhealth issues, disorders, and/or disease. “Bio-smart mirror” refers to amirror, such as may be used in a bathroom and/or bedroom for personalgrooming, for example, that may incorporate one or more sensors (e.g.,camera, microphone, etc.) and one or more processors, such as abehavioral processing unit. In an embodiment, a bio-smart mirror mayinclude one or more cameras that may operate in a substantiallyalways-on mode in at least some circumstances. In an embodiment, due atleast in part to the sensitive nature of what may be captured by amirror (e.g., nudity), a bio-smart mirror may not include networkconnectivity, in an embodiment. In an embodiment, a bio-smart mirror mayaccess bio-ledger and/or biosphere content pertaining to a particularindividual via an intermediary device, such as intermediary device 700.From an intermediary device, such as intermediary device 700, abio-smart device, such as a bio-smart mirror, may obtain a subset ofomic content, such as relevant genetic single nucleotide polymorphisms(SNP), epigenetic markers, and/or doctor-described objectives, forexample. In an embodiment, an individual, for example, may utilize anintermediary device, such as intermediary device 700, to transfer omiccontent, such as one or more bio-ledger and/or biosphere ledger entries,from a secure storage device, such as secure storage device 400, to abio-smart device, such as a non-networked bio-smart mirror.

Further, in an embodiment, a bio-smart mirror may collect sensor contentfrom which an individual's behavior may be inferred, at least in part.For example, a bio-smart mirror may generate two-dimensional imagecontent, three-dimensional image content, etc. In an embodiment, abio-smart mirror may generate one or more control signals as part of aresource allocation operation based, at least in part, on bio-ledgerand/or biosphere ledger content obtained from an intermediary device,such as intermediary device 700. For example, if bio-ledger and/orbiosphere ledger content obtained from an intermediary device indicatesa genetic mutation at BRCA1 and/or BRCA2 (markers determined to beassociated with breast cancer), a bio-smart mirror may focus computing,storage, and/or energy resources, for example, on a task of monitoringand/or predicting breast cancer. Further, for example, if the bio-ledgerand/or biosphere content indicates genetic and/or epigenetic markersrelated to depression, resources may be focused on monitoring depressionand/or risk of suicide. In an embodiment, when focusing on breast-canceridentification, a bio-smart mirror may store a few nude images that maybe useful for that specific task. When focusing on depression and/orrisk of suicide, for example, the mirror might forgo storage of nudeimages and/or may store content related to wardrobe color and/or tone.That is, in embodiments, resources may be allocated to improve accuracyfor personalized, bio-ledger content-guided and/or prioritized tasks.Further, privacy may be promoted due at least in part to non-utilizedcontent being discarded, in an embodiment.

In an embodiment, determinations and/or predictions made by a bio-smartdevice, such as bio-smart device 900, may be logged directly to anintermediary device, such as intermediary device 700, for laterinterpretation at a secure storage location, such as at a healthcareprovider location, for example, without sharing personal, confidential,and/or sensitive content over a network. In this manner, directbio-smart device-to-doctor communication may be supported, for example.

Embodiments may provide a number of advantages over other technologies.For example, it may be unrealistic to expect individuals to manuallyinput relatively large amounts of content, such as epigenetic content,and/or to understand which content might be relevant for particulartasks and/or operations that may be accomplished via an electronicdevice. Therefore, rather than having individuals input epigeneticcontent to any number of various electronic devices that may seek tooperate on such epigenetic content, embodiments may obtain epigeneticcontent from a centralized storage facility, such as secure storagedevice 400, for example, and/or from an intermediary device, such asintermediary device 700. Additionally, because a individual's epigeneticand/or other omic content may change over time, it would be unfeasibleto expect an individual to input entries whenever additional epigeneticand/or other omic content is generated and/or otherwise available. Also,because, for at least some embodiments, user input of epigenetic contentmay not be implemented, some embodiments may not include a userinterface and/or may include a relatively more simple interface.Further, embodiments may limit epigenetic content communicated to anelectronic device to an actionable subset of content, thus maintainingimproved levels of privacy.

Issues related to security of personal, sensitive, and/or confidentialcontent, such as epigenetic content, may provide motivation for one ormore aspects of various embodiments. For example, improved and/oradditional measures may be taken to help ensure legitimate and/orresponsible utilization and/or communication of personal, sensitive,and/or confidential content. In an embodiment, an electronic device,such as a secure storage device 400, a bio-smart device 900, and/or anintermediary device 700, may undergo a certification process prior todistribution in the field. For example, by pre-certifying a deviceand/or by assigning a certified identifier to a device and/or bypermitting access to personal, sensitive, and/or confidential content ata certification time, a mechanism may be implemented to restrict accessto a subset of content for a particular purpose. In an embodiment, acertification process may include agreements in the use of particularcontent. For example, a certification process may include an agreementnot to sell and/or distribute specified content. Further, in anembodiment, a tokenized security parameter, such as may be communicationvia an intermediary device, for example, may expire and/or may be becomeunavailable to a device, such as a bio-smart device, upon disconnectionof an intermediary device, thereby terminating a device's ability tofurther access stored content. Of course, subject matter is not limitedin scope in these respects.

FIG. 10 is an illustration of an embodiment 1000 of an example processfor detecting and/or predicting a change in omic state utilizing, atleast in part, a bio-smart device, such as bio-smart device 900, with agoal of identifying one or more steps an individual may take to helpavoid and/or to help reduce adverse consequences of detected and/orpredicted omic state changes in the individual. Embodiments inaccordance with claimed subject matter may include all of blocks1010-1060, fewer than blocks 1010-1060, and/or more than blocks1010-1060. Further, the order of blocks 1010-1060 is merely an exampleorder, and subject matter is not limited in scope in these respects. Asdepicted at blocks 1010, epigenetic and/or other omic content, such asin the form of bio-ledger content, may be gathered, generated, and/orotherwise obtained for one or more individuals. Biosphere ledger contentmay also be gathered, generated, and/or otherwise obtained for one ormore individuals, as depicted at block 1020. Embodiments may furtheremploy environmental sensors and/or medical (e.g., genetic, biological,etc.) testing to gather, over a period of time, epigenetic content, suchas bio-ledger, and/or content representative of environmental factors,such as one or more biosphere ledger entries, for one or moreindividuals. Epigenetic and/or environmental content for one or moreindividuals may be configured in a manner relatively more conducive toidentification of relationships, correlations, etc. between epigeneticchanges and/or environmental factors. As mentioned, a bio-smart device,such as bio-smart device 900 may obtain bio-ledger and/or biosphereledger content pertaining to a particular individual at least in partvia communication with an electronic device, such as secure storagedevice 400 and/or intermediary device 700. For example, bio-ledgerand/or biosphere content may be transmitted over a network, such as theInternet, via wired and/or wireless communication of signal packetsand/or signal frames, such as between communication interface 420 ofsecure storage device 400 and communication interface 920 of bio-smartdevice 900. Further, for example, bio-ledger and/or biosphere contentobtained from a secure storage device, for example, may be stored assignals and/or states in one or more non-transitory memories, such asmemory 930.

Further, as depicted at block 1030, behavioral profile content may begenerated and/or otherwise obtained. As mentioned, a bio-smart device,such as bio-smart device 900, may generate behavioral profile contentbased at least in part on content, such as signals and/or states,obtained from one or more sensors, such as sensors 950. For example,content obtained from one or more sensors, such as sensors 950, may beprocessed by particular hardware circuitry, such as BPU 1200 and/or ML940, to generate behavioral profile content representative of aparticular individual's physical, mental, and/or emotional state. In anembodiment, behavioral profile content may include a plurality ofparameters representative of focal point, excitement, anger, fear,fatigue, dehydration, or focus/distraction, or any combination thereof,in relation to a particular individual. Behavioral profile content mayfurther include, by way of additional non-limiting examples, parametersrepresentative of pre-breakthrough, silent like (e.g., impliedsatisfaction by an individual with respect to particular consumedcontent), regret, error acknowledgment, hunger, sloppiness/precision,empathy, and/or social engagement level, or any combination thereof.Particular circuitry, such as BPU 1200, is described below in connectionwith generation of behavioral profile content and/or with processing ofsensor content.

As depicted at block 1040, for example, epigenetic and/or other omiccontent, such as bio-ledger content and/or biosphere ledger content forone or more particular individuals, along with behavioral profilecontent for one or more particular individuals, may be analyzed and/orotherwise processed at least in part to detect and/or predict changes inepigenetic state for one or more individuals. In an embodiment,epigenetic and/or behavioral profile content, for example, may beanalyzed and/or otherwise processed at least in part utilizing BPU 1200,processor 910, and/or ML 940. In an embodiment, machine learning and/orother analytic techniques may process time-stamped entries from abio-ledger and/or biosphere ledger for one or more particularindividuals and/or may process behavioral profile content correspondingat particular points in time to one or more time-stamped bio-ledgerand/or biosphere ledger entries, such as content 932 and/or 934, toidentify relationships and/or correlations, for example, betweenbio-ledger and/or biosphere ledger content and behavioral profilecontent. Further, a bio-smart device, such as bio-smart device 900, maydetect and/or predict, at least in part, a change in epigenetic and/orother omic state for one or more particular individuals. In anembodiment, a detection and/or prediction of a change in epigeneticand/or other omic state for a particular individual may be based, atleast in part, on one or more identified relationships and/orcorrelations between changes in epigenetic and/or other omic state andchanges in environmental influencers and/or changes in behavioralprofile content. Further, detection and/or prediction of a change inepigenetic and/or other omic state for a particular individual may beaccomplished at least in part utilizing BPU 1200, processor 910, and/orML 940.

As depicted at block 1050, a determination may be made utilizing BPU1200, processor 910, and/or ML 940 as to whether a change in epigeneticand/or other omic state for one or more particular individuals has beendetected and/or predicted. At least in part in response to adetermination that a change in epigenetic and/or other omic state hasbeen detected and/or predicted, one or more recommendations directed toimproving a current and/or future epigenetic and/or other omic state ofone or more particular individuals may be generated utilizing, at leastin part, BPU 1200, processor 910, and/or ML 940, as indicated at block1060. In an embodiment, generated recommendations may be communicated toone or more particular individuals and/or to one or more otherauthorized individuals and/or entities, such as relatives, caregivers,health professionals, insurance companies, etc. In an embodiment,authorization for dissemination of generated recommendations may be madeby one or more particular individuals, such as user 310.

In an embodiment, a device, such as bio-smart device 900, mayperiodically, regularly, and/or occasionally, for example, present anindividual, such as user 310, with one or more brain-game type problemsvia an interface, such as via display 960 and/or via other interfacesthat may interact with bio-smart device 900. For example, audio and/orvideo content may be presented to an individual via a television, phone,tablet, etc., by way of communications interface 920, in an embodiment.In an embodiment, one or more sensors, such as sensors 950, may beutilized to collect behavioral content. A processor, such as BPU 1200,may generate behavioral profile content for a particular individual,such as user 310, based, at least in part, on signals and/or statesobtained from one or more sensors, such as sensors 950. For example,during presentation of a brain-game to an individual (e.g., anindividual may read a passage of text and/or answer particularquestions), sensor content, such as from one or more cameras, forexample, may be gathered, and/or behavioral profile content may begenerated. In an embodiment, behavioral profile content may indicate eyemovement, such as blink duration, darting, blinking rate, ability tofocus, pupil dilation, etc. Additional behavioral profile content may begenerated based, at least in part, on signals and/or states obtainedfrom a microphone sensor. For example, behavioral profile content mayindicate speech tonality, sentiment, volume, frequency, etc.

As mentioned, behavioral profile content, such as may be generated inresponse to brain-game type interactions with an individual, forexample, may be gathered over a period of time. In an embodiment, over aperiod of time, behavioral profile content may be monitored and/ortracked. Changes in epigenetic markers (e.g., as indicated by bio-ledgercontent) may also be monitored and/or tracked. In an embodiment,monitored and/or tracked changes in epigenetic content and/or monitoredand/or tracked behavioral profile content may be provided tomachine-learning devices, systems, and/or processes, and/or may beprovided to other analysis devices, systems, and/or processes. Forexample, via machine-learning training, correlations and/orrelationships between behavioral profile content and epigenetic stateand/or changes in epigenetic markers may be determined. In anembodiment, behavioral profile content may comprise machine learninginputs, and epigenetic state content may comprise machine learningoutput classification. In an embodiment, once trained, amachine-learning device, system, and/or process may detect and/orpredict changes in epigenetic state based at least in part on behavioralcontent. In some embodiments, changes in epigenetic state may bepredicted and/or detected based solely on behavioral profile content,although subject matter is not limited in scope in this respect.Further, as mentioned, embodiments may involve additional and/or othertypes of omic content, such as, for example, microbiome, proteome,metabolome, and/or transcriptome content.

Although embodiments described herein may utilize behavioral profilecontent, such as may be generated via a behavioral processing unit, suchas BPU 1200, subject matter is not limited in this respect. Contentrepresentative of behavior for an individual may be utilized in variousembodiments regardless of show such content may be generated and/orotherwise obtained. Further, although some embodiments described hereindescribe generating behavioral profile content via a behavioralprocessing unit, such as BPU 1200, embodiments may also make use ofbehavioral processing units, such as BPU 1200, to detect and/or predictchanges in omic state. For example, machine learning units in a BPU,such as BPU 1200, may be utilized to identify relationships and/orcorrelations between behavioral profile content and changes in omicstate and/or to detect and/or predict changes in omic state based atleast in part on behavioral profile content.

As mentioned, embodiments including personal bio-ledgers and/orbiosphere ledgers may provide recommended, standardized, and/orotherwise specified manners of tracking, monitoring, storing, and/orrepresenting, for example, an individual's epigenetic content and/orenvironmental influencers such that science and/or analytics, forexample, may continue to determine relationships and/or correlationsbetween an individual's environmental factors and changes in personalbiological content, for example. In embodiments, more frequentbehavioral monitoring to detect and/or predict changes in epigeneticstate, such as via one or more bio-smart devices, may result in ashorter time-to-identification of such changes. Further, behavioralmonitoring, such as via one or more bio-smart devices, may be utilizedto guide relatively more limited, and therefore relatively lessexpensive, epigenetic testing due, at least in part, to indications bybio-smart devices that such testing may be advisable.

Further, embodiments may be implemented not only with human beings inmind, but may also be implemented with an eye to agriculture. Forexample, plants may undergo epigenetic changes as they develop, and/ormay be relatively more heavily dependent on changes in gene expressionin order to respond to environmental stimuli. Further, other epigeneticphenomena may be plant-specific and/or may be agriculturally important.For example, an induction of flowering in plants in response to anexperience of prolonged cold temperatures (e.g., winter) may include aphysiological phenomenon referred to as vernalization, which may have anepigenetic basis. In embodiments, behavioral indicators for a plant,such as a crop, may be measured (e.g., via one or more cameras)relatively less expensively. Behavioral indicators may be utilized, atleast in part, to predict and/or detect changes in a plant's epigeneticstate. In embodiments, predictions and/or detections of changes inepigenetic state may allow farmers, for example, to determine moreappropriate time to harvest, time to fertilize, when to shade, state ofdormancy, etc., to name a few non-limiting examples. In embodiments, abio-smart device, such as bio-smart device 900, may generaterecommendations based on monitored behavioral content pertaining to aparticular crop, for example, with a goal of improving yield, improvingquality, reducing costs, etc.

FIG. 11 is an illustration of an embodiment 1100 of an example device,system, and/or process for processing signals and/or statesrepresentative of epigenetic content and/or behavioral content, inaccordance with an embodiment. In an embodiment, to generate behavioralprofile content, such as behavioral profile content 1140, for aparticular individual, a processor, such as behavioral processing unit1200, may obtain signals and/or states representative of content fromone or more sensors, such as one or more of sensors 1130. Also, in anembodiment, a processor, such as behavioral processing unit 1200, mayprocess sensor content, such as content from one or more of sensors1130, to generate behavioral profile content, such as behavioral profilecontent 1140, for a particular individual. In an embodiment, aprocessor, such as behavioral processing unit 1200, may includebehavioral content processing circuitry. For example, a processor, suchas behavioral processing unit 1200, may include sensor parameterprocessing circuitry, such as circuitry 1110, and/or may include machinelearning acceleration circuitry, such as circuitry 1120, in anembodiment.

In an embodiment, a processor, such as behavioral processing unit 1200,may provide circuitry to generate, at least in part, behavioral profilecontent, such as behavioral profile content 1140, for a particularindividual to be utilized for any of a wide range of possibleapplications, such as example applications described herein. Forexample, in an embodiment, behavioral profile content may be provided toa decision-making device, process, and/or system, such asdecision-making device, system, and/or process 1150. In an embodiment, aprocessor, such as behavioral processing unit 1200, may relatively moreefficiently process signals and/or states obtained from one or morebehavioral, biological, and/or environmental sensors, or a combinationthereof, associated with a particular individual and/or a particularenvironment, for example. In an embodiment, a processor, such asbehavioral processing unit 1200, may calculate probabilities for“hidden” (e.g., emotional and/or biological) states of a particularoperator at least in part by generating behavioral profile content, suchas behavioral profile content 1140, that may be utilized by one or moredevices, systems, and/or processes, such as decision-making device,system, and/or process 1150, for any of a wide range of possiblepurposes.

For example, as mentioned, behavioral profile content for a particularindividual may be tracked, wherein the behavioral profile content mayinclude a plurality of parameters representative of a current behavioralstate or biological state, or a combination thereof, of the particularindividual. Further, in an embodiment, one or more relationships and/orcorrelations between tracked behavioral profile content and bio-ledgerand/or biosphere content 1160 may be determined, for example. Anembodiment may further include generating one or more recommendationsfor actions that may be taken, such as by a user and/or by otherindividuals, for example, to improve of a current and/or futureepigenetic state of a particular individual. In an embodiment, adecision-making system, device, and/or process, such as system 1150, maygenerate one or more recommendations based, at least in part, onbio-ledger and/or biosphere content 1160 and/or based, at least in part,on behavioral profile content 1140. Further, in an embodiment,recommendations may be made, at least in part, utilizing behavioralprocessing unit 1200. Additionally, in an embodiment, user input 1170may be obtained for any of a range of purposes. For example, anindividual, such as user 310, may provide explicit content related toparticular activities and/or substances consumed, for example. Further,an individual, such as user 310, may provide input, such as user input1170, to configure, guide, and/or focus one or more aspects ofepigenetic and/or behavioral profile content processing, in anembodiment. Of course, subject matter is not limited in scope in theserespects.

In an embodiment, machine-based decision-making, such as decision-makingdevice, system, and/or process 1150, may, for example, include dynamicrecommendation of particular activities, dietary supplementation and/ormodification, etc., for a particular individual with a goal of improvinga current and/or subsequent state of the particular individual. In anembodiment, dynamic recommendation of particular activities, dietarysupplementation and/or modification, etc., for a particular individualmay be based, at least in part, on behavioral profile content and/or maybe based, at least in part, on bio-ledger and/or biosphere ledgercontent 1160. In an embodiment, sensor content may comprise content fromany of a wide range of possible sources and/or that may be variable. Inan embodiment, a processor, such as behavioral processing unit 1200, mayincorporate machine-learning (e.g., neural networks, etc.) at least inpart to adapt to the presence and/or absence of one or more particularsensors while providing probabilities, for example, represented at leastin part by behavioral profile content.

In an embodiment, machine-based decision-making, such as may beperformed by decision-making device, system, and/or process 1150, forexample, may depend at least in part on a individual's current stateand/or a individual's ability to relatively quickly respond to changesin the individual's state. A wide range of possible sensor types mayprovide content representative of various aspects of a particularoperator's biological and/or behavioral state, and/or representative ofone or more environmental factors and/or other external factors. In anembodiment, a processor, such as behavioral processing unit 1200, mayinclude a sensor parameter processing unit, such as sensor parameterprocessing unit 1110. In an embodiment, a sensor parameter processingunit, such as sensor parameter processing unit 1110, may obtain signalsand/or states from one or more sensors, such as sensors 1130, and/or mayprocess signals and/or states from one or more sensors to combine,coordinate, normalize and/or otherwise condition signals and/or statesfrom one or more sensors.

Further, a sensor parameter processing unit, such as sensor parameterprocessing unit 1110, may prepare sensor content for further processing,such as via machine learning operations. In an embodiment, machinelearning acceleration circuitry, such as machine learning accelerationcircuitry 1120, may, at least in part, process sensor content to infer asubstantially current biological and/or behavioral state of a particularoperator. For example, a camera sensor and/or the like may provide oneor more signals and/or states to a sensor parameter processing unit,such as sensor parameter processing unit 1110. Sensor parameterprocessing unit 1110 may generate one or more parameters representativeof pupil dilation, focal point, blink duration, and/or blink rate, orany combination thereof, for example.

In an embodiment, machine learning acceleration circuitry, such asmachine learning acceleration circuitry 1120, may generate, at least inpart, a representation of a particular operator's biological and/orbehavioral state, such as behavioral profile content 1140. In anembodiment, behavioral profile content, such as behavioral profilecontent 1140, may comprise a specified set of parameters that may beutilized by any of a wide range of machine-based (e.g., computingdevice-based) decision making systems, devices, and/or processes, suchas decision-making device, system, and/or process 1150. In anembodiment, behavioral profile content may include a plurality ofparameters representative of focal point, excitement, anger, fear,fatigue, dehydration, or focus/distraction, or any combination thereof,in relation to a particular individual. Behavioral profile content mayfurther include, by way of additional non-limiting examples, parametersrepresentative of pre-breakthrough, silent like, regret/erroracknowledgment, hunger, sloppiness/precision, empathy, and/or socialengagement level, or any combination thereof.

In an embodiment, behavioral profile content may comprise a specifiedset of parameters, such as at least a subset of those mentioned above,for example. In an embodiment, a processor, such as behavioralprocessing unit 1200, may generate a set of parameters representative ofbehavioral profile content specified in a manner so as to providecontent regarding a particular individual's behavioral and/or biologicalstate to any of a wide range of devices, systems, and/or processes forany of a wide range of purposes and/or applications. Further, such a setof specified behavioral profile content parameters may be utilizedconcurrently by any number of devices, systems, and/or processes.

In an embodiment, a processor, such as behavioral processing unit 1200,may repetitively obtain sensor content and/or may repetitively generatebehavioral profile content for a particular individual. For example,sensor content may be gathered and/or otherwise obtained at regularand/or specified intervals, and/or behavioral profile content may begenerated at regular and/or specified intervals. In an embodiment, oneor more devices, systems, and/or processes may track behavioral profilecontent over a period of time, for example, such as to detect changes inbehavioral profile content, for example. Similarly, in an embodiment,one or more devices, systems, and/or processes may track bio-ledgerand/or biosphere content over a period of time, for example.

In an embodiment, a processor, such as behavioral processing unit 1200,may be advantageously utilized at least in part by dedicating computingresources to process sensor content, for example, and/or to generatebehavioral profile content, such as 1140, for a particular individual.Further, by generating a specified set of parameters comprisingbehavioral profile content, such as 1140, systems, devices, and/orprocesses may be relieved of responsibility for generating behavioralprofile content and may, for example, concentrate on particular areas ofexpertise and/or specialization, for example. Further, development costsmay be reduced for systems, devices, and/or processes at least in partdue to having a specified set of behavioral profile content parametersavailable from a processor, such as behavioral processing unit 1200.

In an embodiment, a processor, such as behavioral processing unit 1200,may merge substantially real-time sensor content (e.g., behavioraland/or biological sensor content, or a combination thereof) withrepresentations of prior relationships (e.g., known and/or determinedconnections between that which may be measured and/or human states).Also, in an embodiment, a processor, such as behavioral processing unit1200, may utilize machine learning techniques (e.g., neural networks,etc.) to map incoming sensor content representative of one or moreaspects of an operator's biological and/or behavioral state. In anembodiment, a processor, such as behavioral processing unit 1200, mayinclude support for relatively more efficient coordination and/orprocessing of content obtained from a wide range of possible sources(e.g., combination of content from biological and/or behavioral sensorsand/or content representative of other factors) to generate a specifiedset of parameters, such as behavioral profile content 1140. Further, inan embodiment, one or more memory devices may be provided to storeoperator-dependent and/or operator-independent content to enablerelatively quicker identification of state changes in a particularindividual.

In an embodiment, machine learning operations such as may be performedby a processor, such as behavioral processing unit 1200, for example,may store user-specific content in one or more memory devices and/or mayalso store user-generic content (e.g., determined and/or substantiallyknown relationships between sensor content and/or user states). In anembodiment, user-specific content and/or user-generic content may beprocessed, such as via machine learning operations, to generate one ormore output state vectors, such as behavioral profile content 1140.

In an embodiment, one or more external factors may come in to play withrespect to generating behavioral profile content and/or decision-making.For example, one or more parameters indicative of one or more externalfactors may be obtained by a behavioral profile unit, such as BPU 1200,and/or by a decision-making device, system, and/or process, such asdecision-making system 1150. Parameters representative of externalfactors may include, for example, parameters representative of location,time of day, presence and/or identity of external individual, and/orgeneral sentiment.

FIG. 12 is an illustration of an embodiment 1200 of an example device,system, and/or process, such as a behavioral processing unit (BPU), forprocessing signals and/or states representative of epigenetic contentand/or behavioral content. An embodiment, such as BPU 1200, may includea processor, such as a BPU 1200, to process signals and/or statesrepresentative of behavioral content in a computing device. In anembodiment, to generate behavioral profile content, such as behavioralprofile content 1221, for a particular individual, such as user 1210, aprocessor, such as behavioral processing unit 1200, may obtain signalsand/or states representative of content from one or more sensors, suchas one or more of sensors 1240. Also, in an embodiment, a processor,such as behavioral processing unit 1200, may process sensor content,such as content from one or more of sensors 1240, to generate behavioralprofile content, such as behavioral profile content 1221, for aparticular individual. In an embodiment, a processor, such as behavioralprocessing unit 1200, may include behavioral content processingcircuitry. For example, a processor, such as behavioral processing unit1200, may include sensor content processing circuitry, such as circuitry1222, and/or may include machine learning circuitry, such as circuitry1224 and/or 1226, in an embodiment. In an embodiment, a processor, suchas BPU 1200, may further obtain content from sensors, such as sensors1240, to track one or more environmental aspects (e.g., environmentalsound, temperature, barometric pressure, altitude, location, etc.).

In an embodiment, a processor, such as behavioral processing unit 1200,may provide circuitry to generate, at least in part, behavioral profilecontent, such as behavioral profile content 1221, for a particularindividual, such as user 1210, to be utilized for any of a wide range ofpossible applications and/or purposes. For example, a processor, such asbehavioral processing unit 1200, may generate behavioral profilecontent, such as behavioral profile content 1221, to, at least in part,to identify changes in epigenetic state within a human body, forexample. In an embodiment, behavioral profile content, such asbehavioral profile content 1221, may include one or more parametersindicative of eye movement, voice and/or speech aspects, environmentalsounds, etc. Of course, subject matter is not limited in scope in theserespects.

In an embodiment, one or more sensors, such as sensors 1240, may providecontent representative of various aspects of a particular operator'sbiological and/or behavioral state, and/or representative of one or moreenvironmental factors and/or other external factors. In an embodiment,sensors 1240 may include one or more sensors of one more sensor types,as previously mentioned. Further, in an embodiment, a processor, such asbehavioral processing unit 1200, may include circuitry, such ascircuitry 1222, to process content obtained from one or more sensors,such as sensors 1240. In an embodiment, content obtained from sensors,such as sensors 1240, may include digital signals and/or states, analogsignals and/or states, or any combination thereof. For example,circuitry 1222 may include digital circuitry, analog circuitry, or acombination thereof. In an embodiment, sensor content processingcircuitry, such as circuitry 1222, may convert one or more analogsignals to digital signals, although subject matter is not limited inscope in this respect. In an embodiment, circuitry, such as circuitry1222, may process signals and/or states from one or more sensors, suchas sensors 1240, to combine, coordinate, normalize, amplify, filter,and/or otherwise condition signals and/or states from one or moresensors, such as sensors 1240, although subject matter is not limited inscope in these respects.

Further, in an embodiment, a processor, such as behavioral processingunit 1200, may include circuitry for determining and/or selectingweighting parameters and/or for determining and/or selecting particularmachine learning devices, systems, and/or processes. For example,circuitry 1224 may determine and/or select one or more particularmachine learning techniques, such as one or more particular neuralnetworks and/or including one or more weighting parameters, for example,for use in machine learning operations. In an embodiment, determinationand/or selection of weighting parameters and/or machine learningoperations, including one or more neural networks, for example, may bebased, at least in part, on content, such as parameters 1260,representative of bio-ledger and/or biosphere content pertaining to aparticular individual, such as user 1210.

In an embodiment, machine learning circuitry such as machine learningcircuitry 1226 may, at least in part, process content, such as contentthat may be obtained from circuitry 1222 and/or 1224, to determine,estimate, and/or infer, for example, one or more parametersrepresentative of a substantially current biological and/or behavioralstate of a particular individual. In an embodiment, machine learningcircuitry, such as machine learning circuitry 1226, may generate, atleast in part and/or with contribution from output generation circuitry1228, a representation of a particular individual's biological and/orbehavioral state, such as behavioral profile content 1221. In anembodiment, behavioral profile content, such as 1221, may include aplurality of parameters representative of focal point, excitement,anger, fear, fatigue, dehydration, or focus/distraction,pre-breakthrough, silent like, regret/error acknowledgment, hunger,sloppiness/precision, empathy, or social engagement level, or anycombination thereof, for example. In an embodiment, a processor, such asbehavioral processing unit 1200, may repetitively and/or substantiallyperiodically obtain sensor content and/or may repetitively and/orsubstantially periodically generate behavioral profile content, such asbehavioral profile content 1221, for a particular individual, such asuser 1210. Further, as mentioned, behavioral profile content, such asbehavioral profile content 1221, may include one or more parametersindicative of voice tonality, voice sentiment, volume, frequency, pitch,timbre, etc. Further, as also mentioned, behavioral profile content,such as behavioral profile content 1221, may include one or moreparameters representative of eye darting, blinking rate, ability tofocus, and/or pupil dilation, to name a few additional non-limitingexamples.

In an embodiment, a processor, such as behavioral processing unit 1200,may determine appropriate weights for various sensor combinations and/orfor particular parameters, such as bio-ledger and/or biosphere ledgercontent 1260, during offline training operations, for example. Inanother embodiment, during online operation, for example, a set ofinputs may be logged and/or later used as training parameters. Forexample, an individual, such as user 1210, may explicitly provide inputsrelated to supplementation and/or consumption of particular substancesand/or may provide inputs related to particular behaviors for aparticular individual, for example. Further, in an embodiment,determined and/or substantially known relationships, such asrelationships represented by parameters 1250, may include relationshipsbetween behavioral profile content and/or user states and/or may includescientifically determined relationships. For example, scientificpublications may provide research results indicative of relationshipsbetween changes in epigenetic and/or other omic state and particularenvironmental and/or behavioral factors. In an embodiment, parameters1254 representative of other relationships may be determined acrossmultiple individuals and/or across populations, for example.

FIG. 13 is an illustration of an embodiment 1300 an example device,system, and/or process for processing signals and/or statesrepresentative of epigenetic content and/or behavioral content, inaccordance with an embodiment. For example, FIG. 13 includes a schematicblock diagram depicting an embodiment 1300 of an example device, such asa behavioral processing unit, for processing content, such as contentobtained from sensors 1330, to generate signals and/or statesrepresentative of behavioral content in a computing device. In anembodiment, a behavioral processing unit, such as BPU 1300, may beimplemented in a bio-smart device, such as bio-smart device 900, in asecure storage device, such as secure storage device 400, and/or in anyof a wide range of electronic device types, for example. Further, in anembodiment, a behavioral processing unit, such as BPU 1300, may beutilized to process epigenetic content in connection with behavioralprofile content, while in other embodiments a behavioral processingunit, such as BPU 1300, may operate on epigenetic content in the absencebehavioral content.

In an embodiment, a processor, such as behavioral processing unit 1300,may process digital signals and/or states or analog signals and/orstates, or a combination thereof (e.g., mixed-signal). Any of a widerange of digital and/or analog circuit types may be utilized to processdigital, analog, and/or mixed-signal signals and/or states, as explainedmore fully below. In an embodiment, one or more aspects of a processor,such as behavioral processing unit 1300, may be implemented to operatein an analog domain, while one or more other aspects may be implementedto operate in a digital domain. In other embodiments, a processor, suchas behavioral processing unit 1300, may be implemented to operatesubstantially wholly in the digital domain and/or the analog domain.

In an embodiment, a processor, such as behavioral processing unit 1300,may, in general, substantially continuously obtain content from sensors,such as one or more sensors 1330, and/or may substantially continuouslygenerate output signals and/or states, such as behavioral profilecontent 1325. Generated output signals and/or states, such as behavioralprofile content 1325, may be made available to one or moredecision-making systems, such as decision-making system 1340, forexample. In an embodiment, a decision-making device, system, and/orprocess, such as decision-making system 1340, may determine, at least inpart via at least one processor performing one or more machine learningoperations, one or more relationships between tracked behavioral profilecontent, such as behavioral profile content 1325 and bioavailabilityand/or balance, or a combination thereof, of one or more particularsubstances within a particular individual's body. An embodiment mayfurther include a decision-making device, system, and/or process, suchas decision-making system 1340, to analyze and/or otherwise processbehavioral profile content, such as content 1325, in combination withepigenetic content, such as bio-ledger and/or biosphere content 1311,for example, to detect and/or predict changes in epigenetic state forone or more individuals. Further, in embodiments, content, such asbehavioral profile content for one or more individuals, may be analyzedand/or otherwise processed in combination with epigenetic content, forexample, to generate recommendations with respect to one or moreindividuals. In embodiments, recommendations may be directed atimproving a current and/or future epigenetic state of one or moreindividuals. In other embodiments, content, such as behavioral profilecontent for a particular individual, may be analyzed and/or otherwiseprocessed in combination with epigenetic content, for example, togenerate recommendations for a particular individual directed to theparticular individual's behavioral and/or biological state.

In an embodiment, a sensor parameter processing stage, such as sensorparameter processing stage 1301, may obtain signals and/or states (e.g.,digital, analog, and/or mixed-signal) from one or more sensors, such assensors 1330. In an embodiment, a sensor parameter processing stage,such as sensor parameter processing stage 1301, may process signalsand/or states from one or more sensors at least in part by combiningcontent, adjusting timing, performing noise reductions and/or othersignal reduction operations, normalizing content, or any combinationthereof, for example. However, subject matter is not limited in scope inthis respect.

Further, in an embodiment, sensor content steering circuitry, such assensor content steering circuitry 1317, may direct signals and/or statesobtained from sensors, such as from sensors 1330, to one or more sensorprocessing units, such as one or more of sensor processing units (SPU)1305. In an embodiment, sensor processing units, such as SPUs 1305, maybe configured via one or more control signals, such as control signalscommunicated between a control unit, such as control unit 1303, andsensor processing units, such as SPUs 1305. Sensor processing units,such as SPUs 1305, may prepare sensor content, such as signals and/orstated obtained from one or more sensors, such as sensors 1330, forfurther processing by, for example, a machine-learning processing stage,such as machine-learning processing stage 1302. In an embodiment, sensorcontent steering circuitry, such as sensor content steering circuitry1317, may direct content based, at least in part, on one or more controlsignals obtained from a control unit, such as control unit 1303, and/orfrom a memory, such as memory 1312, for example.

In an embodiment, a sensor processing stage, such as sensor processingstage 1301, may include one or more sensor processing units, such assensor processing units 1305, that may be configured to operateindividually or in one or more various combinations. Sensor processingunits, such as SPUs 1305, may perform, individually and/or incooperation, any of a variety of operations that may be specified and/orimplemented. Such operations may include, for example, combining signalsand/or states, adjusting timing of signals and/or states, performingnoise reductions and/or other signal reduction operations, and/ornormalizing content, to list but a few examples.

One or more sensor processing units, such as SPUs 1305, may beimplemented to operate in an analog domain and/or one or more units maybe implemented to operate in a digital domain. In an embodiment,sensors, such as sensors 1330, may provide signals and/or statescomprising analog signals and/or comprising digital content (e.g.,signals and/or states). Further, in an embodiment, one or more analogsignals obtained by one or more sensors, such as 1330, may be convertedto digital content using analog-to-digital conversion circuitry. Inother embodiments, analog signals obtained from sensors, such as sensors1330, for example, may be maintained as analog signals for processing byone or more sensor processing units, such as SPUs 1305. Further, in anembodiment, individual sensor processing units, such as SPUs 1305, maybe implemented in analog and/or digital based, at least in part, onparticular tasks to be performed by a particular SPU and/or based, atleast in part, on particular signal types to be obtained from sensors,such as sensors 1330. In an embodiment, one or more of a variety offilters, signal amplifiers, and/or signal damping circuits, ranging fromrelatively more simple to relatively more complex, for example, may beperformed by one or more particular sensor processing units, such asSPUs 1305. Sensor processing unit operations, such as example operationsmentioned herein, may have particular relevance in a larger context ofbehavioral profile content generation in connection with one or moremachine-learning units. For example, sensor processing unit operationsmay be performed with an end-goal of behavioral profile contentgeneration in mind.

In an embodiment, a particular sensor processing unit, such as SPU 1305,may include noise reduction, filtering, dampening, combining, amplifyingcircuitry, etc., for example, implemented to operate in the analogdomain. Analog circuitry may include, for example, one or more op-amps,transistors, capacitors, resistors, etc., although subject matter is notlimited in scope in this respect. Circuitry, such as noise reduction,filtering, dampening, combining, amplifying circuitry, etc., forexample, may also be implemented in the digital domain, or in acombination of analog and/or digital. For another example, a particularsensor processing unit, such as a particular SPU 1305, may beimplemented in analog and/or digital to combine signals and/or states.In an embodiment, a unit to combine signals and/or states may beimplemented in the analog domain or in the digital domain, or acombination thereof. In an embodiment, analog hysteretic“winner-take-all” circuits may be implemented at least in part toimprove noise robustness and/or to mitigate, at least in part, timingdifference between sensor input streams, for example. Of course, subjectmatter is not limited in scope in these respects. Further, noisereduction, filtering, dampening, combining, and/or amplifying are merelyexample tasks that may be performed by one or more sensor processingunits, such as SPUs 1305, and, again, subject matter is not limited inscope in these respects.

Further, in an embodiment, sensor processing units, such as SPU 1305,may be implemented to generate outputs that may exhibit a range ofapproximation, imprecision, and/or non-replicability. In an embodiment,machine-learning units, such as ML 1306, may help mitigate consequencesthat might otherwise occur due to approximation, imprecision, and/ornon-replicability potentially exhibited by sensor processing units, suchas SPU 1305. As utilized herein, “replicable” in the context of sensorprocessing units, such as SPU 1305, refers to an ability to generate thesame output for a given duplicate set of inputs. “Non-replicability” inthis context refers to one or more sensor processing units, such as SPU1305, not necessarily generating the same output for a given duplicateset of inputs. That is, in an embodiment, one or more sensor processingunits, such as SPU 1305, may be implemented in a manner so as to notguarantee similar outputs for similar sets of inputs.

In an embodiment, content steering circuitry, such as content steeringcircuitry 1318, may direct content, such as signals and/or states,generated by one or more sensor processing units, such as SPUs 1305, toa machine-learning stage, such as machine-learning stage 1302. Content,such as signals and/or states 1321, generated by one or more sensorprocessing units, such as SPUs 1305, may also be stored, at leasttemporarily, in a memory, such as memory 1316, for example. In anembodiment, memory 1316 may comprise a buffer, such as a first-in,first-out buffer, for example, although subject matter is not limited inscope in this respect. In an embodiment, content steering circuitry,such as content steering circuitry 1318, may direct content based, atleast in part, on one or more control signals obtained from a controlunit, such as control unit 1303, and/or from a memory, such as memory1312, for example.

A machine-learning stage, such as machine-learning stage 1302, mayinclude content steering circuitry, such as content steering circuitry1308, that may direct content, such as signals and/or states 1321,obtained from a sensor processing stage, such as sensor processing stage1301, to one or more machine-learning units (ML), such asmachine-learning units 1306, for example. In an embodiment, contentsteering circuitry, such as content-steering circuitry 1308, may directcontent, such as signals and/or states 1321, based, at least in part, onone or more control signals obtained from a control unit, such ascontrol 1303, and/or from a memory, such as memory 1313.

In an embodiment, machine-learning units, such as machine-learning units1306, may be configured via one or more control signals, such as controlsignals communicated between a control unit, such as control unit 1303,and machine-learning units, such as machine-learning units 1306. In anembodiment, one or more machine-learning units, such as machine-learningunits 1306, may be configured to operate individually or in onecombination with one or more other machine-learning units. In anembodiment, individual machine-learning units, such as machine-learningunits 1306, may implement particular machine-learning techniques.Further, one or more machine-learning units, such as machine-learningunits 1306, may be implemented to operate in the analog domain or in thedigital domain, or a combination thereof. For example, amachine-learning unit operating in the analog domain may include voltageand/or current summing circuits to sum a number of signals and/or statesand/or may include devices, such as variable impedance devices, that mayapply weighting factors to individual signals and/or states. Of course,subject matter is not limited in scope in these respects.

Content steering/selecting circuitry, such as content steering/selectingcircuitry 1307, may select and/or combine content generated by one ormore machine-learning units, such as machine-learning units 1306, in anembodiment. Further, content steering/selecting circuitry, such ascontent steering/selecting circuitry 1307, may direct output, such assignals and/or states representative of behavioral profile content 1325,to a decision-making system, such as decision-making system 1340. In anembodiment, a control unit, such as control unit 1303, may obtain atleast a portion of the output generated by machine-learning units, suchas machine-learning units 1306.

In an embodiment, control unit, such as control unit 1303, may configureand/or control one or more aspects of behavioral processing unit 1300.In an embodiment, a control unit, such as control unit 1303, may obtaininputs from a variety of sources and/or may control various aspects ofbehavioral processing unit 1300 based, at least in part, on the obtainedinputs. In an embodiment, control unit inputs may be obtained from unitswithin behavioral processing unit 1300 unit itself and/or from one ormore other sources. For example, control unit 1303 may obtain userparameters 1315 (e.g., user ID or other parameters descriptive of aparticular user). In an embodiment, user parameters, such as parameters1315, may be obtained from an individual and/or from one or moreexternal sources and/or may be obtained from one or more memories withinbehavioral processing unit 1300. For example, user parameters for one ormore particular users may be stored in a memory, such as memory 1304. Inan embodiment, one or more parameters, such as parameters 1315, may beobtained, for example, from an intermediary device, such as intermediarydevice 700. Further, in an embodiment, one or more parameters, such asparameters 1315, may be obtained, for example, from a secure storagedevice, such as secure storage device 400.

Various aspects of behavioral processing unit 1300 may be configuredand/or reconfigured based at least in part on parameters that may bestored on an individual user basis in a memory, such as memory 1304. Forexample, a control unit, such as control unit 1303, may communicate witha memory, such as memory 1304, to obtain configuration content for aparticular user from memory 1304, and/or may configure behavioralprocessing unit 1300 based at least in part on the obtainedconfiguration content. Further, in an embodiment, a control unit, suchas control unit 1303, may obtain content from a decision-making system,such as decision-making system 1340, or from one or more externalsources, such as secure storage system 1350. In an embodiment, one ormore bio-ledger and/or biosphere entries may be obtained, for example,from a secure storage device, such as secure storage 1350.

Although example behavioral processing unit 1300 is depicted havingparticular memory devices, such as memories 1304, 1312, 1314, and/or1316, other embodiments may include memory elements distributed invarious areas of the processing unit. For example, memory elements maybe included in one or more sensor processing units 1305 and/or in one ormore machine-learning units 1306. Additionally, a memory, such as memory1304, may be implemented as a hierarchy of memory devices and/ortechnologies that may allow for various sizes and/or memory accessspeeds. Further, a memory, such as memory 1304, may storemachine-learning weighting parameters and/or other machine-learningparameters, and/or may also store control signals, for example.

In an embodiment, a control unit, such as control unit 1303, maygenerate one or more output signals and/or states, such as one or morecontrol signal, based, at least in part, on inputs obtained by thecontrol unit. Control signal output generation may be a function of oneor more inputs that may include, for example, user identificationparameters, content type parameters, contextual parameters, taskparameters, sensor availability parameters, or behavioral profilecontent specification parameters, bio-ledger and/or biosphere content,such as content 1311, or any combination thereof. Of course, these aremerely example types of inputs that may be obtained by a control unit,such as control unit 1303, and subject matter is not limited in scope tothese particular examples.

As mentioned, a control unit, such as control unit 1303, may obtain userparameters 1315 that may include user identification content and/orother parameters descriptive of a particular user). Further, in anembodiment, a control unit, such as control unit 1303, may obtainparameters, such as parameters 1314, descriptive of substances ingestedand/or otherwise consumed by a user (e.g., foods, vitamins, medicines,lotions, creams, cosmetics, soaps, shampoo, etc.). Control unit 1303 mayfurther obtain parameters descriptive of a task being performed by auser, or parameters descriptive of context and/or environment, or anycombination thereof, for example. Further, in an embodiment, contentand/or task parameters 1310 may be provided by and/or obtained from adecision-making system, such as decision-making system 1340. Forexample, parameters descriptive of user and/or task may indicate a typeof task being performed (e.g., walking, flying, driving, performingsurgery, etc.) and/or may indicate a particular user. Also, for example,parameters descriptive of context and/or environment may indicate aparticular setting (e.g., location, time of day, date, etc.), presenceof other individuals, or other contextual information, or anycombination thereof.

A control unit, such as control unit 1303, may also obtain parameters,such as parameters 1314, that may be indicative of sensor availability,for example. Additionally, a control unit, such as control unit 1303,may obtain parameters, such as parameters 1319, that may indicate one ormore particular parameters and/or parameter types of behavioral profilecontent, such as behavioral profile content 1325, to be generated on arelative priority basis, for example, by machine-learning stage 1302,for example. Further, one or more parameters 1320 representative of oneor more aspects of behavioral profile content 1325 generated bymachine-learning stage 1302 may be provided to and/or obtained by acontrol unit, such as control unit 1303. For example, parameters 1320may include feedback to control unit 1303 that may influence behavioralprocessing unit operations, in an embodiment.

As mentioned, a control unit, such as control unit 1303, may generateone or more control signals based, at least in part, on inputs that maybe obtained from any of a range of sources. For example, inputs obtainedby control unit 1303 may allow for selecting particular content from oneor more memory elements, such as one or more of memories 1304, 1312,1314, and/or 1316, to be utilized in configuring sensor processing stage1301 and/or machine-learning stage 1302 for processing. For example,sensor processing stage 1301 and/or machine-learning stage 1302 may beconfigured based on a particular user, a particular task, or aparticular context, or a combination thereof. By tailoring processing inthis manner, improved behavioral profile content may be generated,and/or efficiency may be improved (e.g., improved confidence ofbehavioral profile content while utilizing relatively fewer resources).Further, in an embodiment control unit 1303 may steer outputs of sensorprocessing stage 1301 (e.g., intermediary results) to particularmachine-learning units 1305 via control of steering circuitry 1308based, at least in part, on inputs obtained by control unit 1303.Similarly, control unit 1303 may select output from one or moreparticular machine-learning units 1306 via control of steering/selectingcircuitry 1307 based, at least in part, on obtained inputs. Further,weighting of inputs for machine-learning units 1306 may be determined atleast in part based on obtained inputs. For example, a control unit,such as control unit 1303, may steer, select, and/or weight intermediaryresults (e.g., content generated by sensor processing stage 1301) as afunction of user identification, task type, environmental context, orsensor availability, or any combination thereof, in an embodiment. Ofcourse, subject matter is not limited in scope in these respects.

Further, in an embodiment, resource allocation within a processor, suchas behavioral processing unit 1300, may be based, at least in part, onbehavioral profile content specification parameters, such as parameters1319. In an embodiment, a control unit, such as control unit 1303, mayobtain behavioral profile content specification parameters 1319 that mayindicate one or more behavioral profile parameters to be relativelyprioritized, for example, and may select particular sensor processingunits 1305 and/or particular machine-learning units 1306 based, at leastin part, on the specified behavioral profile content parameters.“Relatively prioritized” in the context of behavioral profile contentspecification parameters, such as parameters 1319, refers to one or moreparticular parameters to be processed on a priority basis over otherparameters. For example, behavioral profile content specificationparameters 1319 may indicate an “anger” parameter. Resources (e.g., SPUs1305, machine-learning units 1306, memory, etc.) sufficient to processthe “anger” parameter to a particular confidence level, for example, maybe allocated, even at the expense of resources that may otherwise beallocated to generating other behavioral profile content parameters.Control unit 1303 may, via one or more control signals, select resourcesfrom sensor processing stage 1301 and/or machine-learning stage 1302 togenerate behavioral profile content in accordance with the specifiedparameters. In this manner, relatively prioritized content may begenerated relatively more efficiently. Behavioral profile contentspecification parameters, such as parameters 1319, may also indicaterelative priorities related to trade-offs between power consumption andgeneration of particular behavioral profile content, in an embodiment.Further, in an embodiment, relatively prioritized content may begenerated at the relative expense of other behavioral profile content.For example, behavioral profile parameters indicating anger and/orfatigue may be relatively prioritized over excitement and/or hungerparameters, and control unit 1303 may configure sensor processing stage1301 and/or machine-learning stage 1302 accordingly. Further, in anembodiment, self-feedback and/or output monitoring content, such ascontent 1320, may allow for control adjustments, such as selectingadditional/different machine-learning units and/or sensor processingunits and/or otherwise adjusting resource utilization within behavioralprocessing unit 1300. Such adjustments may be made, for example, to meetspecified relative priorities, specified levels of confidence ingenerated output, etc.

In addition to allocating resources based, at least in part, onparticular parameters related to behavioral profile content processing,other embodiments may allocate resources based, at least in part, onparticular bio-ledger and/or biosphere parameters, such as particularparameters from bio-ledger and/or biosphere content 1311, for example.

Although some embodiments described herein mention neural networktechniques for machine learning, subject matter is not limited in scopein this respect. Other embodiments may incorporate other machinelearning techniques either presently existing or to be developed in thefuture. Further, for embodiments implementing neural networks, forexample, sensors may be removed from a system during offlinepre-deployment training operations such that a neural network maydetermine appropriate weights for various sensor combinations. Inanother embodiment, during online operation, for example, a set of inputbiomarkers may be logged and/or later used as training parameters,wherein a predicted behavioral processing unit output may be utilized atleast in part to train one or more networks that may lack some subset ofthe initial inputs. For online inference, an appropriate neural networkmay be selected based at least in part on available sensor inputs. Suchan arrangement may be advantageous in situations wherein an operator mayremove one or more sensors from a system, device, and/or process. Forexample, during surgery, a surgeon may remove his or her glasses thatmay have been tracking eye movement. In an embodiment, a differentneural network configuration may be selected at least in part inresponse to such a change in available sensor input, for example. Forexample, a control unit, such as control unit 1303, may detect a changein sensor availability (e.g., signified by sensor availability input1314), and/or may reconfigure sensor processing units 1305 and/ormachine-learning units 1306 based at least in part on the detectedchange in sensor availability.

FIG. 14 is an illustration of an embodiment 1400 of an example processfor generating recommendations directed to improvement of a futureepigenetic fitness state of a particular individual. Embodiments inaccordance with claimed subject matter may include all of blocks1410-1430, fewer than blocks 1410-1430, and/or more than blocks1410-1430. Further, the order of blocks 1410-1430 is merely an exampleorder, and subject matter is not limited in scope in these respects. Inembodiments, an individual's bio-ledger and/or biosphere ledger contentmay have value beyond a single lifetime. For example, epigenetic and/orother omic markers may be inherited by future offspring, epigeneticand/or other omic content may be relevant to those with similar healthlandscapes and/or situations (e.g., family members, relatives, etc.),and/or epigenetic and/or other omic content may be useful forpopulation-level science and/or for future study and/or analysis, toname but a few non-limiting examples. Therefore, benefits of omic and/orbehavioral content processing have a potential to span generations. Inan embodiment, a potential benefit of epigenetic and/or other omiccontent processing and/or behavioral content processing may include anability to measure progress toward “Epigenetic Fitness” goals. Forexample, a prospective parent may desire to set one or more goalsrelated to epigenetic fitness.

With an increased knowledge of epigenetic, epigenetic inheritance,and/or transgenerational epigenetic inheritance, and/or with decreasesin costs of epigenetic testing, individuals may be motivated to changeone or more habits to improve their epigenetic state. For example,individuals may desire to improve their intelligence markers and/or toremove addiction markers, not only for themselves, but also for thebenefit of future offspring, for example. Similar to the industry aroundphysical fitness, an emergence of “epigenetic fitness” in the generalpopulation and/or among prospective parents may occur, particularlysince physical fitness and fertility represent relatively very largemarkets. In an embodiment, an example device, system, and/or process forproviding an epigenetic fitness score may allow for an individual tomonitor progress toward a particular specified epigenetic fitness goal.

As depicted at block 1410, one or more particular epigenetic parametersdetermined to be indicative of a particular epigenetic fitness state maybe identified. For example, a processor, such as BPU 1200, processor910, and/or ML 940, may obtain an input from an individual, for example,wherein the input may indicate a particular fitness goal of interest tothe individual. That is, in an embodiment, a particular individual mayspecify a particular goal. For example, an individual may indicate adesire for increased athletic performance abilities. An individual mayinteract with a user interface of a computing device, such as bio-smartdevice 900 and/or secure storage device 400, for example, althoughclaimed subject matter is not limited in scope in these respects.Further, as depicted at block 1420, one or more particular omicparameters for a particular individual may be compared with theidentified one or more particular epigenetic parameters determined to beindicative of a particular fitness goal. In an embodiment, thecomparison may be performed, for example, by a processor, such as BPU1200, processor 910, and/or ML 940. For example, a subset of epigeneticmarkers having a determined and/or known relationship to theindividual's specified goal (e.g., epigenetic markers associated withathletic performance), may be extracted and/or otherwise obtained fromthe individual's bio-ledger. For example, a computing device, such abio-smart device 900, may receive signal packets and/or signal framescomprising bio-ledger content, for example, over a network from a securestorage device, such as secure storage device 400. Further, in anembodiment, the individual's epigenetic markers may be compared to thedesired markers based at least in part on the specified goal. Again, forexample, a processor, such as BPU 1200, processor 910, and/or ML 940,may perform the comparison. In an embodiment, a score may be generatedby a processor, such as BPU 1200, processor 910, and/or ML 940, based,at least in part, on a measure of similarity between the individual'sparticular markers and the desired markers. In an embodiment, adetermination of a measure of similarity may be based, at least in part,on any of a number of possible distance metrics. Various parametersand/or markers may be weighted based, at least in part, on a determinedimportance factor for a particular marker, in an embodiment.

In an embodiment, as indicated at block 1430, one or morerecommendations for a particular individual may be generated based, atleast in part, on a comparison of the individual's markers and thedesired markers, and/or based at least in part on one or more behavioralprofile parameters, or a combination thereof, wherein one or morerecommendations are substantially directed to improvement of a futureepigenetic fitness state of the particular individual. For example, inan embodiment, an individual's biosphere ledger may be analyzed by aprocessor, such as BPU 1200, processor 910, and/or ML 940, to providerecommendations for influencing desired markers. In an embodiment,analyzation of an individual's biosphere ledger may be based, at leastin part, on machine learning-identified relationships via populationscience. Further, in an embodiment, this example process may continue atspecified intervals to provide an individual with updated epigeneticfitness scores and/or with updated recommendations.

In some situations, progress towards health and/or fitness goals forindividuals may be measured according, at least in part, to relativelyinferior metrics such as weight, body-mass index, exercise time, and soforth. Embodiments described herein introduce utilization of epigeneticmarkers to monitor progress towards fitness and/or health goals.Further, embodiments may provide relatively more refined metrics thatmay provide improved accuracy with respect to progress, as well asprovide content regarding health predispositions that may be passed onto future offspring.

FIG. 15a is an illustration of an embodiment 1500 of an examplelogging-type device. As mentioned, devices may comprise a “logging” typedevice, wherein particular content may be logged to one or moreparticular individual's biosphere ledger and/or bio-ledger. Asmentioned, a public logging-type device may log biosphere and/orbio-ledger content intended to be shared across a population ofindividuals, in an embodiment. On the other hand, a private loggingdevice may log bio-ledger and/or biosphere entries pertaining to aparticular individual. In an embodiment, a logging-type device, such aslogging-type device 1500, may include one or more sensors, such assensors 1550, that may log measurements pertaining to one or moreparticular individuals to a memory, such as memory 1530. A memory, suchas memory 1530, may store, for example, bio-ledger entries 1534 and/orbiosphere entries 1532.

In an embodiment, logging of content to a particular individual'sbiosphere ledger and/or bio-ledger may occur at least in part inresponse to an individual, such as user 310, coming into proximity ofthe logging-type device and/or at least in part in response to anintermediary device, such as intermediary device 700, being electricallyconnected to a logging-type device, such as logging-type device 1500.For example, an individual, such as user 310, may carry an intermediarydevice, such as intermediary device 700, within a specified distance ofa logging-type device, such as logging-type device 1500. Also, in anembodiment, a logging-type device, such as logging-type device 1500, mayidentify a particular intermediary device and/or a particular individualbased, at least in part, on one or more wireless signals communicatedbetween an intermediary device, such as intermediary device 700, and alogging-type device, such as logging-type device 1500.

FIG. 15b depicts an example communication of bio-ledger and/or biosphereledger content. In an embodiment, bio-ledger content, such as entries1534, and/or biosphere ledger content, such as entries 1532, may becommunicated between a logging-type device, such as logging-type device1500, and any of a wide range of devices, systems, and/or processes. Forexample, content, such as content 333 including one or more bio-ledgerentries 1534 and/or one or more biosphere entries 1532, may becommunicated via one or more wired and/or wireless communicationnetworks between a computing device, such as logging-type device 1500,and one or more other devices, such as secure storage device 400 and/orintermediary device 700. In an embodiment, a logging-type device, suchas device 1500, may include a communications interface, such ascommunication interface 1520, and may further include a processor, suchas processor 1510. In an embodiment, logged entries, such as entries1532 and/or 1534, may be communicated via utilization of a processor,such as processor 1510, and/or a communication interface, such ascommunication interface 1520. Of course, subject matter is not limitedin scope in these respects.

In further embodiments, a logging-type device, such as logging-typedevice 1500, may comprise an industrial-scale logging-type device. Asmentioned, industrial-scale logging-type devices may process epigeneticand/or other omic content, behavioral profile content, and/orenvironmental content related to multiple particular individuals, and/ormay access/write to bio-ledgers and/or biosphere ledgers pertaining tomultiple particular individuals, for example.

FIG. 16, for example, is an illustration of an embodiment 1600 of anexample system for processing signals and/or states representative ofepigenetic and/or other omic content across a population of individuals.In an embodiment, a system, such as example system 1600, may include aplurality of logging-type devices, such as logging-type devices 1500,for example. In an embodiment, logging-type devices, such aslogging-type devices 1500, may communicate via wired and/or wirelessnetwork signals with a storage device, such as secure storage 400. Forexample, one or more logging-type devices, such as logging-type devices1500, may transfer one or more parameters indicative of bio-ledgerand/or biosphere content for one or more particular individuals fromlogging-type devices 1500 to secure storage device 400. For example,logging-type devices 1500 may write bio-ledger content and/or biospherecontent for one or more individuals to storage 490, in an embodiment. Inanother embodiment, biosphere ledger entries, for example, may notpertain to particular individuals but may instead pertain across apopulation of individuals. In an embodiment, a storage device, such assecure storage device 400, may store copies of public and/or generalbiosphere ledger entries in particular biosphere ledgers for particularindividuals based at least in part on the particular individual's GPSlocation content, for example. In an embodiment, a logging-type device,such as logging-type device 1500, may store an identifier forintermediary devices detected to have come within a particular proximityof the logging-type device, for example. Based at least in part on thestored identifiers, a logging-type device, such as logging-type device1500, for example, may facilitate communication of appropriate biosphereledger entries from a logging-type device, such as logging-type device1500, and a secure storage device, such as secure storage device 400,such that a secure storage device, such as secure storage device 400,may store the appropriate biosphere ledger entries in appropriateindividuals' biosphere ledgers, in an embodiment.

In an embodiment, one or more individuals, such as user 310, may carryand/or wear, for example, one or more respective intermediary devices,such as intermediary devices 700. One or more intermediary devices 700may come into proximity with one or more logging-type bio-smart devices,such as bio-smart devices 1500. At least in part in response to adetection of one or more intermediary devices 700, one or morelogging-type bio-smart devices 1500 may store one or more measurements,for example, in an onboard memory, such as memory 1530. Further, in anembodiment, one or more logging-type bio-smart devices 1500 may initiatecommunication of one or more measurements, for example, between the oneor more bio-smart devices 1500 and secure storage 400 so thatmeasurement content may be stored in database 490. Further, asintermediary devices 700 are transported around a geographical area, forexample, multiple logging-type devices may be encountered, and/ormultiple measurement parameters may be communicated and/or stored. Overa period of time, for example, a number of measurements for a number ofindividuals may be gathered and/or may be stored, for example, at asecure storage device, such as secure storage device 400. Further,particular changes to epigenetic and/or other omic markers forparticular individuals may be detected, and/or patterns involving largernumbers of individuals may be detected, at least in part via aprocessor, such as processor 410 of secure storage device 400, in anembodiment.

FIG. 17 is an illustration of an embodiment 1700 of an example processfor detecting locations associated with undesirable changes inepigenetic state. Embodiments in accordance with claimed subject mattermay include all of blocks 1710-1740, fewer than blocks 1710-1740, and/ormore than blocks 1710-1740. Further, the order of blocks 1710-1740 ismerely an example order, and subject matter is not limited in scope inthese respects.

Devices, systems, and/or processes, such as bio-smart devices 900 and/orother types of devices, may be utilized, in an embodiment, to monitor,track, and/or otherwise gather bio-ledger and/or biosphere ledgercontent across a population of individuals. In an embodiment, locationparameters associated with biosphere ledger entries, for example, may beutilized in conjunction, at least in part, with bio-ledger content overa group of individuals to identify and/or predictgeographically-significant events. For example, trends in changes toepigenetic state for a plurality of individuals may be tracked within aparticular geographical area. In an embodiment, content representativeof changes in epigenetic state for particular individuals within apopulation (e.g., bio-ledger content) may be correlated and/or otherwiseassociated with particular content identifying particular locationswithin a geographical area (e.g., biosphere ledger content) to detectand/or predict geo-graphically significant events. By linking relativelyfine-grained location parameters to epigenetic content, example devices,systems, and/or processes may identify and/or predictsocietally-significant events such as, for example, an introduction ofenvironmental toxins (e.g., lead contamination, air pollutants, etc.),an introduction of food supply contaminations (e.g., via identificationof early-onset puberty), and/or an increase in addiction rates (e.g.,opioid over-distribution). Of course, these are merely examples, andsubject matter is not limited in scope in these respects.

Herein, a particular location determined to be associated with a trendand/or pattern of adverse changes in epigenetic state over a populationof individuals may be referred to as a “geographic hotspot.” In anembodiment, bio-smart devices, such as bio-smart device 900, may beutilized, at least in part, to determine geographic hotspots. Forexample, machine-learning, such as ML 940 and/or BPU 1200 and/or BPU1300, may be utilized to identify, at least in part, a trend and/orpattern of changes in epigenetic state for individuals of a populationof individuals, wherein the trend and/or pattern of changes inepigenetic state are associated with one or more particular locationswithin a geographical area. However, although some embodiments mayutilize bio-smart devices, such as bio-smart device 900, and/orbehavioral processing units, such as BPUs 1200 and/or 1300, to identifygeographical hotspots, other embodiments may utilize, at least in part,other types of electronic devices. In some embodiments,machine-learning, such as performed by ML 940, BPU 1200, and/or BPU1300, for example, may be utilized, at least in part, to identifygeographic hotspots. However, in other embodiments, other types ofprocessing and/or analysis may be utilized, at least in part, toidentify geographical hotspots.

In general, to identify epigenetic geographic hotspots, a computingdevice, such as secure storage device 400 and/or bio-smart device 900,may attach relatively fine-grained location parameters to anindividual's omic content (e.g., epigenetic test content, environmentalinfluencer content, etc.) at least in part by accessing an individual'sbio-ledger and/or biosphere ledger. In an embodiment, a bio-smartdevice, such as bio-smart device 900, may read from and/or write to anindividual's bio-ledger and/or biosphere ledger at least in part viawired and/or wireless communication of signal packets and/or signalframes over a network. In an embodiment, location parameters mayrepresent locations which an individual may have visited and/or at whichan individual may have resided, for example. In an embodiment, locationparameters may be based, at least in part, on satellite positioningsystem location content (e.g., GPS location content). In an embodiment,attaching and/or otherwise associating location parameters to epigeneticcontent may be performed by a processor, such as processor 410, for anumber of individuals across a population of individuals. Further, ingeneral, trends in epigenetic and/or other omic state changes acrossindividuals of a population may be monitored. In an embodiment,individuals of a population may be related according to location. Thatis, for example, individuals located, either temporarily and/or moreregularly, in a particular geographic region may be considered apopulation of individuals, in an embodiment. Additionally, in general,prior knowledge regarding epigenetic markers (e.g., epigenetic markersassociated with addiction, environmental toxins, etc.) and theirrelationships to health may be utilized to identify societally-relevantphenomena occurring in a geographic region. In an embodiment, such priorknowledge may be gleaned, at least in part, from bio-ledger and/orbiosphere ledger content for a number of individuals. In an embodiment,geographic hotspots may be determined for one or more particularlocations (e.g., particular factory, restaurant, park, home, office,etc.). In other embodiments, geographic hotspots may be determined for alocation representative of a geographic area (e.g., particularneighborhood, city, county, etc.). Of course, subject matter is notlimited in scope in these respects.

Returning to FIG. 17, an embodiment 1700 of an example process fordetecting geographical hotspots is illustrated. As depicted at block1710, omic content representative of a plurality of particularepigenetic states corresponding to respective points in time for aplurality of individuals may be obtained, wherein the omic contentincludes parameters indicative of particular bio-markers associated withparticular gene expressions. In an embodiment, omic and/or epigeneticcontent may be obtained by a secure storage device, such as securestorage device 400, at least in part by receiving, at communicationsinterface 420, signal packets and/or signal frames, for example,transmitted over a network, such as the Internet. In an embodiment,epigenetic and/or other omic content may be obtained at least in part byreceiving signal packets and/or signal frames from test lab computingdevices, doctor office computing devices, etc. In an embodiment, omicand/or other epigenetic content may be stored as one or more bio-ledgerentries and/or one or more biosphere entries, for example. In anembodiment, bio-ledger entries and/or biosphere entries may be stored,for example, as signals and/or states in one or more non-transitorymedia and/or memories and/or mass storage devices of a secure storagedevice, such as secure storage device 400. Further, as indicated atblock 1720, one or more parameters indicative of particularenvironmental conditions, including user location, associated with theparticular omic states and identified approximately at one or more ofthe respective points in time may also be obtained. In an embodiment,omic and/or epigenetic content may be obtained by a secure storagedevice, one or more parameters indicative of particular environmentalconditions, including user location, associated with the particular omicstates may be obtained, at least in part by receiving, at communicationsinterface 420, for example, signal packets and/or signal framestransmitted over a network, such as the Internet.

Further, in an embodiment, as indicated at block 1730, one or morerelationships between one or more changes in epigenetic state for one ormore of the plurality of individuals and one or more particularenvironmental conditions may be identified utilizing a processor, suchas BPU 1200, processor 910, and/or ML 940, based, at least in part, onthe epigenetic content or the parameters indicative of the particularenvironmental conditions, or a combination thereof. Also, in anembodiment, one or more locations associated with undesirable changes inepigenetic states for at least a specified threshold number ofindividuals may be detected based at least in part on the one or moreidentified relationships, as performed at least in part by a processor,such as BPU 1200, processor 910, and/or ML 940.

In some situations, problems such as environmental toxins may bediscovered to occur, for example, based on sufficient numbers of peoplebecoming ill, exhibiting symptoms, seeking help, etc. Embodimentsdescribed herein may be advantageously utilized to identifylocation-based trends relatively more quickly. Further, embodiments mayallow for identification of trends that may ordinarily go unnoticed byan individual (e.g., early-onset puberty, inability to concentrate inchildren, etc.). Further, embodiments wherein location parameters may beassociated and/or otherwise linked with epigenetic content may allow forrelatively more directed and/or efficient allocation of resources aimedat addressing societally-relevant issues related to a geographic region.For example, a problem of resource allocation for addiction and/orsuicide prevention may be addressed, in an embodiment. Also, forexample, embodiments may support identification of geographical regionshaving increasing addiction rates, thereby allowing for relatively moreaccurate identification of regions for increased resource allocation.Again, subject matter is not limited in scope in these respects.

FIG. 18 is an illustration of an example process for identifyingpatterns of proteome changes, microbiome changes, metabolome,transcriptome, and/or epigenetic changes that may lead to adverseiatrogenic consequences. As utilized herein, “proteome” refers to a setof proteins expressed by a genome, cell, tissue, and/or organism at aparticular point in time. “Proteome content” and/or the like refers todigital content, such as signals and/or states, representative of one ormore aspects of proteome. Further, “microbiome” refers to combinedgenetic material of a community. In humans, for example, microbiomerefers to genes of microbes that may exist within a particularindividual. “Microbiome content” and/or the like refers to content, suchas signals and/or states, representative of one or more aspects ofmicrobiome. “Transcriptome” refers to a set of messenger RNA moleculesexpressed from the genes of an organism and/or “metabolome” refers to aset of metabolites present within an organism, for example.Additionally, “iatrogenic” relates to illness caused, at least in part,by medical examination and/or treatment.

In general, for an embodiment, content, such as proteome, microbiome,metabolome, transcriptome, and/or epigenetic content, may be collectedand/or otherwise obtained at a point of an initial healthcare-relatedintervention and again at a point of a secondary point ofhealthcare-related intervention wherein the secondary intervention wasdirected at addressing a negative consequence of the prior intervention.Machine learning and/or other analysis techniques may be utilized toidentify patterns of epigenetic and/or microbiome changes associatedwith adverse and/or negative iatrogenic consequences. Examples ofinitial healthcare-related interventions may include, but are notlimited to, dental implantation, newly administered medication within apsychiatric and/or medical situation, and/or recommendation of aparticular behavioral regiment, such as an elite athletic trainingroutine. Again, subject matter is not limited in scope in theserespects.

In some situations, some patients may suffer from negative and/oroccasionally irreversible effects that may manifest over time due to aninteraction with a healthcare provider. Iatrogenic effects such as thesemay be of particular concern to healthcare providers. For example,healthcare providers may wish to avoid situations where secondinterventions may be needed to address negative consequences of anearlier intervention. By collecting proteome, microbiome, metabolome,transcriptome, and/or epigenetic content at the point of and/orsubstantially immediately prior to an initial intervention and again ata point of secondary intervention, for example, machine learning and/orother analysis techniques may be utilized, at least in part, to identifya pattern of epigenetic and/or other omic changes associated with anadvisability for a secondary intervention. Once trained, amachine-learning device, system, and/or process, for example, may signalto a healthcare professional, for example, that a secondary interventionmay be advisable in a for a particular individual based at least in parton an identification of similar patterns in changes to epigenetic,microbiome, and/or proteome content. In an embodiment, proteome,microbiome, metabolome, transcriptome, and/or epigenetic content may bestored as bio-ledger entries, for example.

Embodiments may provide any of several example advantages, including apotential to identify a situation before a damaging consequence mayoccur, a possibility of identification a situation without additionalhealthcare professional invention (e.g. via mail-in epigenetic testing)in situations wherein a subsequent intervention may be beneficial,and/or a possibility of identification without reliance on subjective(e.g., patient-reported) content. In many situations, doctors, forexample, may manage responsibility for iatrogenic consequences throughfollow-up visits in which subjective patient reporting of undesirableconsequences and/or diagnostic testing, such as blood testing, providescontent related to an advisability for a secondary intervention.Additional situations may arise wherein iatrogenic consequences may notbe actively managed. In such situations, for example, handling ofiatrogenic responsibilities via subjective reporting and/or otherdiagnostic tests may lead to an undesirable situation of identifyingadvisability for secondary intervention after, rather than prior, to anonset of undesirable consequences. Additionally, additional proteome,microbiome, metabolome, transcriptome, and/or epigenetic testing betweena first intervention and a second intervention may allow for tracking amore detailed progression of changes which may lead to even earlieridentification of an advisability for a secondary intervention.

In embodiments, epigenetic testing, for example, may present anopportunity to track additional patient-related content due at least inpart to epigenetic changes having been shown to occur at least in partin response to changes in environment, including environmental changesdue to healthcare provider intervention. In some situations, however,the sheer number of possibilities related to such changes may limitidentification of particular epigenetic patterns to well-researcheddisease states. Embodiments, such as one or more of those describedherein, may provide an opportunity to monitor an individual's body'sreaction to environmental changes associated with a healthcare-relatedintervention, and/or to identify a desirability for a secondaryintervention prior to onset of negative and/or otherwise undesirableconsequences.

Returning to FIG. 18, an embodiment 1800 of an example process foridentifying patterns of proteome changes, microbiome changes, metabolomechanges, transcriptome changes, and/or epigenetic changes that may leadto adverse iatrogenic consequences is depicted. Embodiments inaccordance with claimed subject matter may include all of blocks1810-1840, fewer than blocks 1810-1840, and/or more than blocks1810-1840. Further, the order of blocks 1810-1840 is merely an exampleorder, and subject matter is not limited in scope in these respects. Asdepicted at block 1810, a first set of epigenetic parameters, microbiomeparameters, metabolome, transcriptome, or proteome parameters, or acombination thereof, may be obtained for a plurality of individuals atpoints in time of first healthcare-related interventions for theplurality of individuals. For example, omic test results for a pluralityof individuals may be stored as signals and/or states in a database,such as a bio-ledger and/or biosphere ledger, for one or moreindividuals at a secure storage device, such as secure storage device400. Additionally, as indicated at block 1820, a second set ofepigenetic parameters, microbiome parameters, or proteome parameters, ora combination thereof, may be obtained for a plurality of individuals atpoints in time of second healthcare-related interventions, wherein thesecond interventions may be directed to addressing consequences arisingfrom first interventions. Again, in an embodiment, omic test results fora plurality of individuals may be stored as signals and/or states in adatabase, such as a bio-ledger and/or biosphere ledger, for one or moreindividuals at a secure storage device, such as secure storage device400.

In an embodiment, a machine-learning device, system, or process, or acombination thereof, such a processor 410, BPU 1200, BPU 1300, and/or ML940, for example, may be trained to identify one or more patterns ofchanges in epigenetic parameters, microbiome parameters, metabolomeparameters, transcriptome parameters, or proteome parameters, or acombination thereof, based, at least in part, on the first and secondsets of parameters, as indicated at block 1830. Further, as indicated atblock 1840, an increase in advisability and/or need of a secondintervention for a particular individual may be identified based, atleast in part, on the identified patterns. In an embodiment,identification of an increase in advisability of a second interventionmay be performed, at least in part, by processor, such as BPU 1200,processor 910, and/or ML 940. As mentioned, by identifying situations inwhich a second intervention may be advisable, a healthcare professionalmay take steps to either avoid situations that tend to lead to secondinterventions, and/or may more quickly take steps to reduce negativeand/or otherwise adverse consequences arising from a prior intervention.

Below, various example embodiment are reviewed. As noted, claimedsubject matter is not limited in scope to these specific examples. Asdescribed herein, embodiments may include obtaining epigenetic contentfor a particular individual, wherein the epigenetic content isrepresentative of a plurality of particular epigenetic statescorresponding to respective points in time. Embodiments may furtherinclude tracking behavioral profile content for the particularindividual over a period of time including the respective points intime, training a machine-learning device, system, or process, or acombination thereof, to identify one or more relationships between oneor more particular behaviors and one or more changes in epigenetic statefor the particular individual based, at least in part, on the epigeneticcontent and the behavioral profile content, and identifying a furtherchange in epigenetic state for the particular individual based at leastin part on a detected change in behavioral profile content.

In an embodiment, epigenetic content representative of a plurality ofparticular epigenetic states for a particular individual may include oneor more entries from a bio-ledger for the particular individual, whereinthe bio-ledger includes one or more parameters indicative of particularbio-markers associated with particular gene expression. Epigeneticcontent representative of the plurality of particular epigenetic statesfor a particular individual may also include one or more entries from abiosphere ledger for the particular individual, wherein the biosphereledger includes one or more parameters indicative or particularenvironmental conditions identified approximately at one or more of therespective points in time.

In an embodiment, an apparatus may include at least one processor toobtain signals and/or states representative of behavioral profilecontent for a particular individual, the behavioral profile content toinclude a plurality of parameters representative of a current behavioralstate or biological state, or a combination thereof, of the particularindividual. In an embodiment, at least one processor may further obtainsignals and/or states representative of epigenetic content for aparticular individual, and/or may, at least in part via one or moremachine learning operations, generate one or more recommendations forthe particular individual based at least in part on the behavioralprofile content or based at least in part on the epigenetic content, ora combination thereof. In an embodiment, the one or more recommendationsmay be directed to improvement of a future epigenetic state of theparticular individual.

In an embodiment, epigenetic content for a particular individual mayinclude one or more parameters representative of one or more particularepigenetic states to correspond to one or more particular points intime. Further, one or more parameters representative of the plurality ofparticular epigenetic states may include one or more entries from abio-ledger for the particular individual, wherein the bio-ledger mayinclude one or more parameters indicative of particular bio-markersassociated with particular gene expressions. Also, in an embodiment, atleast one processor may initiate communication of the epigenetic contentfor the particular individual between a server computing device and theat least one processor at least in part via an exchange of one or moresecurity tokens. Further, at least one processor may obtain one or moresecurity tokens from a portable electronic device of the particularindividual.

In other embodiments, an apparatus may include at least one processor toobtain signals and/or states representative of epigenetic content forone or more individuals, wherein the epigenetic content to include oneor more parameters indicative of particular bio-markers associated withparticular gene expressions. An apparatus may also include at least onememory to store the epigenetic content for the one or more individuals,wherein the epigenetic content to be indexed at least in part on aper-user basis. In an embodiment, at least one processor may obtainsignals and/or states representative of environmental factor contentassociated with epigenetic content, wherein at least one memory furtherto store the environmental factor content, and wherein the environmentalfactor content to be indexed at least in part on a per-user basis. Also,in an embodiment, at least one processor may initiate transmission of aparticular security token to a portable computing device of a particularindividual to allow for access to one or more entries of epigeneticcontent associated with the particular individual. Additionally, the atleast one processor to initiate transmission of one or more decryptionkeys to a portable computing device of a particular individual to allowfor decryption of the one or more entries of epigenetic contentassociated with the particular individual.

In an embodiment, an apparatus may further include an external deviceport, wherein at least one processor to initiate transmission of one ormore security tokens at least in part in response to a physicalattachment of the portable computing device to the external device port.At least one processor may further initiate transmission of a specifiedsubset of epigenetic content associated with the particular individualto a networked device at least in part in response to a request from thenetworked device, wherein the request to include the particular securitytoken.

In a further embodiment, an apparatus may include at least one processorto obtain a security token from a server computing device, wherein thesecurity token to provide particular permission to access one or moreparticular entries of epigenetic content associated with a particularindividual stored at the server computing device. An apparatus may alsoinclude at least one memory to store the security token, and at leastone sensor to detect proximity to a particular external device, whereinthe at least one processor to initiate transmission of the securitytoken to the external device at least in part in response to thedetection of proximity. Further, in an embodiment, at least oneprocessor may obtain one or more particular entries of epigeneticcontent from the server computing device, and the at least one memorymay store the one or more particular entries. Also, at least oneprocessor may initiate transmission of at least a subset of the one ormore entries to the external device at least in part in response to thedetection of proximity. In an embodiment, at least one sensor mayinclude a local wireless network transceiver, and at least one processormay initiate transmission of the security token via the local wirelessnetwork transceiver.

An additional embodiment may include identifying one or more particularepigenetic parameters determined to be indicative of a particularfitness state, storing signals and/or states representative of theidentified one or more particular epigenetic parameters in at least onememory, comparing, utilizing at least one processor, one or moreparticular epigenetic parameters for a particular individual with theidentified one or more particular epigenetic parameters determined to beindicative of a particular fitness goal, and generating, via the atleast one processor based at least in part on one or more machinelearning operations, one or more recommendations for the particularindividual based at least in part on the comparing or based at least inpart on one or more behavioral profile parameters, or a combinationthereof, wherein the one or more recommendations are substantiallydirected to improvement of a future epigenetic fitness state of theparticular individual.

Further, embodiments may include obtaining, utilizing at least oneprocessor, epigenetic content representative of a plurality ofparticular epigenetic states corresponding to respective points in timefor a plurality of individuals, wherein the epigenetic content toinclude parameters indicative of particular bio-markers associated withparticular gene expressions, obtaining, utilizing the at least oneprocessor, one or more parameters indicative of particular environmentalconditions, including user location, associated with the particularepigenetic states and identified approximately at one or more of therespective points in time, storing the epigenetic content or theparameters indicative of the particular environmental conditions, or acombination thereof, in at least one memory, identifying, via amachine-learning device and/or system, one or more relationships betweenone or more changes in epigenetic state for one or more of the pluralityof individuals and one or more particular environmental conditionsbased, at least in part, on the epigenetic content or the parametersindicative of the particular environmental conditions, or a combinationthereof, and detecting, at least in part via the machine-learning deviceand/or system, one or more locations associated with undesirable changesin epigenetic states for at least a specified threshold amount ofindividuals based at least in part on the one or more identifiedrelationships. Embodiments may also include generating, via themachine-learning device and/or system, one or more recommendations basedat least in part on the one or more identified relationships, whereinthe one or more recommendations are directed to improvement of futureepigenetic states of at least the plurality of individuals.

An additional embodiment may include obtaining, utilizing at least oneprocessor, a first set of epigenetic parameters, microbiome parameters,or proteome parameters, or a combination thereof, for a plurality ofindividuals at points in time of first healthcare-related interventionsfor the plurality of individuals, storing the first set of parameters inat least one memory, obtaining, utilizing at least one processor, asecond set of epigenetic parameters, microbiome parameters, metabolomeparameters, transcriptome parameters, or proteome parameters, or acombination thereof, for the plurality of individuals at points in timeof second healthcare-related interventions, wherein the secondinterventions are directed to addressing consequences arising from thefirst interventions, storing the second set of parameters in at leastone memory, training a machine-learning device, system, or process, or acombination thereof, to identify one or more patterns of changes inepigenetic parameters, microbiome parameters, metabolome parameters,transcriptome parameters, or proteome parameters, or a combinationthereof, based, at least in part, on the first and second sets ofparameters, and identifying an increase in advisability and/or need fora second intervention for a particular individual based, at least inpart, on the identified patterns.

An embodiment may also include obtaining one or more additionalepigenetic parameters, microbiome parameters, or proteome parameters, ora combination thereof, for the particular individual, wherein theidentifying the increase in likelihood of the second intervention isbased, at least in part, on the identified patterns and on theadditional parameters.

Embodiments may also be employed in agricultural situations. Forexample, an embodiment may include obtaining epigenetic contentrepresentative of a plurality of particular epigenetic statescorresponding to respective points in time for a particular crop,obtaining from at least one sensor behavioral content for the particularcrop over a period of time including the respective points in time,training a machine-learning device, system, or process, or a combinationthereof, to identify one or more relationships between one or moreparticular behaviors and one or more changes in epigenetic state for theparticular crop based, at least in part, on the epigenetic content andthe behavioral content, and predicting a further change in epigeneticstate for the particular crop based at least in part on a detectedchange in behavioral content. An embodiment may further includegenerating, at least in part via the machine-learning device, system, orprocess, one or more recommendations with respect to time to harvest,time to fertilize, or time to shade, or a combination thereof, for theparticular crop based, at least in part, on the predicted change inepigenetic state.

In a further embodiment, an apparatus may include a weight scale todetect weight of a user, and/or may include at least one memory to storeparameters indicative of user weight measured at particular points intime. In an embodiment, at least one processor may obtain signals and/orstates representative of epigenetic content for a particular user, andmay, at least in part via one or more machine learning operations,generate one or more recommendations for the particular user based atleast in part on the user weight parameters or based at least in part onthe epigenetic content, or a combination thereof, the one or morerecommendations to be directed to improvement of a future epigeneticstate of the particular user. In an embodiment, at least one processormay further obtain content representative of one or more aspects of oneor more scientific publications directed to relationships betweenparticular epigenetic parameters and weight changes, wherein at leastone processor may generate the recommendations based, at least in part,on the user weight parameters, the epigenetic content, or the contentrepresentative of the one or more aspects of one or more scientificpublications, or a combination thereof. In an embodiment, one or morerecommendations may include one or more recommendations to avoid apre-diabetes condition, and/or may include one or more recommendationsto avoid potential adverse effects to future offspring.

One or more other embodiments may include one or more sensors to detectproximity of a plurality of uniquely identified personal computingdevices, the one or more sensors further to detect one or moreparticular environmental conditions at one or more particular points intime, and/or may include at least one memory to store one or moreparameters representative of the one or more particular environmentalconditions at the one or more particular points in time, to storeparameters indicative of identities of the plurality of uniquelyidentified personal computing devices to be detected, and to store timestamp content to indicate times of detection for respective personalcomputing devices. In an embodiment, at least one processor may initiatetransmission of the one or more parameters representative of one or moreparticular environmental conditions, parameters indicative of identitiesof the plurality of uniquely identified personal computing devices,and/or the time stamp content to a biosphere ledger database to comprisea networked computing device. In another embodiment, a logging-typedevice, for example, may log on to an individual's intermediary deviceat least in part to link a generalized biosphere ledger entry to aparticular individual's biosphere ledger, for example. In someembodiments, a logging-type device may transfer a generalize biosphereledger entry to a particular individual's intermediary device, and/orthe intermediary device may be utilized, for example, to transferbiosphere ledger entry content to a secure storage device.

In an embodiment, one or more sensors may include a wireless networkreceiver to detect the proximity of the plurality of uniquely identifiedpersonal computing devices. One or more sensors may also include, forexample, an air quality sensor, wherein one or more parametersrepresentative of the one or more particular environmental conditions atthe one or more particular points in time may comprise one or moreparameters indicative of one or more aspects of air quality measured atthe one or more particular points in time.

In the context of the present patent application, the term “connection,”the term “component” and/or similar terms are intended to be physical,but are not necessarily always tangible. Whether or not these termsrefer to tangible subject matter, thus, may vary in a particular contextof usage. As an example, a tangible connection and/or tangibleconnection path may be made, such as by a tangible, electricalconnection, such as an electrically conductive path comprising metal orother conductor, that is able to conduct electrical current between twotangible components. Likewise, a tangible connection path may be atleast partially affected and/or controlled, such that, as is typical, atangible connection path may be open or closed, at times resulting frominfluence of one or more externally derived signals, such as externalcurrents and/or voltages, such as for an electrical switch. Non-limitingillustrations of an electrical switch include a transistor, a diode,etc. However, a “connection” and/or “component,” in a particular contextof usage, likewise, although physical, can also be non-tangible, such asa connection between a client and a server over a network, whichgenerally refers to the ability for the client and server to transmit,receive, and/or exchange communications, as discussed in more detaillater. Also, the term “connection” may be utilized in a context of aneural network model, and may, in an embodiment, refer to parameterspassed between nodes that may include parameters and/or sets ofparameters representative of output values, for example. Also, in anembodiment, connections between nodes may include weight parameters. Forexample, one or more weight parameters may operate in a specified manneron one or more parameters representative of one or more output values toyield a connection, such as between a node of a first layer and a nodeof a second layer, in an embodiment, for example.

In a particular context of usage, such as a particular context in whichtangible components are being discussed, therefore, the terms “coupled”and “connected” are used in a manner so that the terms are notsynonymous. Similar terms may also be used in a manner in which asimilar intention is exhibited. Thus, “connected” is used to indicatethat two or more tangible components and/or the like, for example, aretangibly in direct physical contact. Thus, using the previous example,two tangible components that are electrically connected are physicallyconnected via a tangible electrical connection, as previously discussed.However, “coupled,” is used to mean that potentially two or moretangible components are tangibly in direct physical contact.Nonetheless, is also used to mean that two or more tangible componentsand/or the like are not necessarily tangibly in direct physical contact,but are able to co-operate, liaise, and/or interact, such as, forexample, by being “optically coupled.” Likewise, the term “coupled” isalso understood to mean indirectly connected. It is further noted, inthe context of the present patent application, since memory, such as amemory component and/or memory states, is intended to be non-transitory,the term physical, at least if used in relation to memory necessarilyimplies that such memory components and/or memory states, continuingwith the example, are tangible.

Additionally, in the present patent application, in a particular contextof usage, such as a situation in which tangible components (and/orsimilarly, tangible materials) are being discussed, a distinction existsbetween being “on” and being “over.” As an example, deposition of asubstance “on” a substrate refers to a deposition involving directphysical and tangible contact without an intermediary, such as anintermediary substance, between the substance deposited and thesubstrate in this latter example; nonetheless, deposition “over” asubstrate, while understood to potentially include deposition “on” asubstrate (since being “on” may also accurately be described as being“over”), is understood to include a situation in which one or moreintermediaries, such as one or more intermediary substances, are presentbetween the substance deposited and the substrate so that the substancedeposited is not necessarily in direct physical and tangible contactwith the substrate.

A similar distinction is made in an appropriate particular context ofusage, such as in which tangible materials and/or tangible componentsare discussed, between being “beneath” and being “under.” While“beneath,” in such a particular context of usage, is intended tonecessarily imply physical and tangible contact (similar to “on,” asjust described), “under” potentially includes a situation in which thereis direct physical and tangible contact, but does not necessarily implydirect physical and tangible contact, such as if one or moreintermediaries, such as one or more intermediary substances, arepresent. Thus, “on” is understood to mean “immediately over” and“beneath” is understood to mean “immediately under.”

It is likewise appreciated that terms such as “over” and “under” areunderstood in a similar manner as the terms “up,” “down,” “top,”“bottom,” and so on, previously mentioned. These terms may be used tofacilitate discussion, but are not intended to necessarily restrictscope of claimed subject matter. For example, the term “over,” as anexample, is not meant to suggest that claim scope is limited to onlysituations in which an embodiment is right side up, such as incomparison with the embodiment being upside down, for example. Anexample includes a flip chip, as one illustration, in which, forexample, orientation at various times (e.g., during fabrication) may notnecessarily correspond to orientation of a final product. Thus, if anobject, as an example, is within applicable claim scope in a particularorientation, such as upside down, as one example, likewise, it isintended that the latter also be interpreted to be included withinapplicable claim scope in another orientation, such as right side up,again, as an example, and vice-versa, even if applicable literal claimlanguage has the potential to be interpreted otherwise. Of course,again, as always has been the case in the specification of a patentapplication, particular context of description and/or usage provideshelpful guidance regarding reasonable inferences to be drawn.

Unless otherwise indicated, in the context of the present patentapplication, the term “or” if used to associate a list, such as A, B, orC, is intended to mean A, B, and C, here used in the inclusive sense, aswell as A, B, or C, here used in the exclusive sense. With thisunderstanding, “and” is used in the inclusive sense and intended to meanA, B, and C; whereas “and/or” can be used in an abundance of caution tomake clear that all of the foregoing meanings are intended, althoughsuch usage is not required. In addition, the term “one or more” and/orsimilar terms is used to describe any feature, structure,characteristic, and/or the like in the singular, “and/or” is also usedto describe a plurality and/or some other combination of features,structures, characteristics, and/or the like. Likewise, the term “basedon” and/or similar terms are understood as not necessarily intending toconvey an exhaustive list of factors, but to allow for existence ofadditional factors not necessarily expressly described.

Furthermore, it is intended, for a situation that relates toimplementation of claimed subject matter and is subject to testing,measurement, and/or specification regarding degree, to be understood inthe following manner. As an example, in a given situation, assume avalue of a physical property is to be measured. If alternativelyreasonable approaches to testing, measurement, and/or specificationregarding degree, at least with respect to the property, continuing withthe example, is reasonably likely to occur to one of ordinary skill, atleast for implementation purposes, claimed subject matter is intended tocover those alternatively reasonable approaches unless otherwiseexpressly indicated. As an example, if a plot of measurements over aregion is produced and implementation of claimed subject matter refersto employing a measurement of slope over the region, but a variety ofreasonable and alternative techniques to estimate the slope over thatregion exist, claimed subject matter is intended to cover thosereasonable alternative techniques unless otherwise expressly indicated.

To the extent claimed subject matter is related to one or moreparticular measurements, such as with regard to physical manifestationscapable of being measured physically, such as, without limit,temperature, pressure, voltage, current, electromagnetic radiation,etc., it is believed that claimed subject matter does not fall with theabstract idea judicial exception to statutory subject matter. Rather, itis asserted, that physical measurements are not mental steps and,likewise, are not abstract ideas.

It is noted, nonetheless, that a typical measurement model employed isthat one or more measurements may respectively comprise a sum of atleast two components. Thus, for a given measurement, for example, onecomponent may comprise a deterministic component, which in an idealsense, may comprise a physical value (e.g., sought via one or moremeasurements), often in the form of one or more signals, signal samplesand/or states, and one component may comprise a random component, whichmay have a variety of sources that may be challenging to quantify. Attimes, for example, lack of measurement precision may affect a givenmeasurement. Thus, for claimed subject matter, a statistical orstochastic model may be used in addition to a deterministic model as anapproach to identification and/or prediction regarding one or moremeasurement values that may relate to claimed subject matter.

For example, a relatively large number of measurements may be collectedto better estimate a deterministic component. Likewise, if measurementsvary, which may typically occur, it may be that some portion of avariance may be explained as a deterministic component, while someportion of a variance may be explained as a random component. Typically,it is desirable to have stochastic variance associated with measurementsbe relatively small, if feasible. That is, typically, it may bepreferable to be able to account for a reasonable portion of measurementvariation in a deterministic manner, rather than a stochastic matter asan aid to identification and/or predictability.

Along these lines, a variety of techniques have come into use so thatone or more measurements may be processed to better estimate anunderlying deterministic component, as well as to estimate potentiallyrandom components. These techniques, of course, may vary with detailssurrounding a given situation. Typically, however, more complex problemsmay involve use of more complex techniques. In this regard, as alludedto above, one or more measurements of physical manifestations may bemodeled deterministically and/or stochastically. Employing a modelpermits collected measurements to potentially be identified and/orprocessed, and/or potentially permits estimation and/or prediction of anunderlying deterministic component, for example, with respect to latermeasurements to be taken. A given estimate may not be a perfectestimate; however, in general, it is expected that on average one ormore estimates may better reflect an underlying deterministic component,for example, if random components that may be included in one or moreobtained measurements, are considered. Practically speaking, of course,it is desirable to be able to generate, such as through estimationapproaches, a physically meaningful model of processes affectingmeasurements to be taken.

In some situations, however, as indicated, potential influences may becomplex. Therefore, seeking to understand appropriate factors toconsider may be particularly challenging. In such situations, it is,therefore, not unusual to employ heuristics with respect to generatingone or more estimates. Heuristics refers to use of experience relatedapproaches that may reflect realized processes and/or realized results,such as with respect to use of historical measurements, for example.Heuristics, for example, may be employed in situations where moreanalytical approaches may be overly complex and/or nearly intractable.Thus, regarding claimed subject matter, an innovative feature mayinclude, in an example embodiment, heuristics that may be employed, forexample, to estimate and/or predict one or more measurements.

It is further noted that the terms “type” and/or “like,” if used, suchas with a feature, structure, characteristic, and/or the like, using“optical” or “electrical” as simple examples, means at least partiallyof and/or relating to the feature, structure, characteristic, and/or thelike in such a way that presence of minor variations, even variationsthat might otherwise not be considered fully consistent with thefeature, structure, characteristic, and/or the like, do not in generalprevent the feature, structure, characteristic, and/or the like frombeing of a “type” and/or being “like,” (such as being an “optical-type”or being “optical-like,” for example) if the minor variations aresufficiently minor so that the feature, structure, characteristic,and/or the like would still be considered to be substantially presentwith such variations also present. Thus, continuing with this example,the terms optical-type and/or optical-like properties are necessarilyintended to include optical properties. Likewise, the termselectrical-type and/or electrical-like properties, as another example,are necessarily intended to include electrical properties. It should benoted that the specification of the present patent application merelyprovides one or more illustrative examples and claimed subject matter isintended to not be limited to one or more illustrative examples;however, again, as has always been the case with respect to thespecification of a patent application, particular context of descriptionand/or usage provides helpful guidance regarding reasonable inferencesto be drawn.

With advances in technology, it has become more typical to employdistributed computing and/or communication approaches in which portionsof a process, such as signal processing of signal samples, for example,may be allocated among various devices, including one or more clientdevices and/or one or more server devices, via a computing and/orcommunications network, for example. A network may comprise two or moredevices, such as network devices and/or computing devices, and/or maycouple devices, such as network devices and/or computing devices, sothat signal communications, such as in the form of signal packets and/orsignal frames (e.g., comprising one or more signal samples), forexample, may be exchanged, such as between a server device and/or aclient device, as well as other types of devices, including betweenwired and/or wireless devices coupled via a wired and/or wirelessnetwork, for example. An example of a distributed computing systemcomprises the so-called Hadoop distributed computing system, whichemploys a map-reduce type of architecture. In the context of the presentpatent application, the terms map-reduce architecture and/or similarterms are intended to refer to a distributed computing systemimplementation and/or embodiment for processing and/or for generatinglarger sets of signal samples employing map and/or reduce operations fora parallel, distributed process performed over a network of devices. Amap operation and/or similar terms refer to processing of signals (e.g.,signal samples) to generate one or more key-value pairs and todistribute the one or more pairs to one or more devices of the system(e.g., network). A reduce operation and/or similar terms refer toprocessing of signals (e.g., signal samples) via a summary operation(e.g., such as counting the number of students in a queue, yielding namefrequencies, etc.). A system may employ such an architecture, such as bymarshaling distributed server devices, executing various tasks inparallel, and/or managing communications, such as signal transfers,between various parts of the system (e.g., network), in an embodiment.As mentioned, one non-limiting, but well-known, example comprises theHadoop distributed computing system. It refers to an open sourceimplementation and/or embodiment of a map-reduce type architecture(available from the Apache Software Foundation, 1901 Munsey Drive,Forrest Hill, Md., 21050-2747), but may include other aspects, such asthe Hadoop distributed file system (HDFS) (available from the ApacheSoftware Foundation, 1901 Munsey Drive, Forrest Hill, Md., 21050-2747).In general, therefore, “Hadoop” and/or similar terms (e.g.,“Hadoop-type,” etc.) refer to an implementation and/or embodiment of ascheduler for executing larger processing jobs using a map-reducearchitecture over a distributed system. Furthermore, in the context ofthe present patent application, use of the term “Hadoop” is intended toinclude versions, presently known and/or to be later developed.

In the context of the present patent application, the term networkdevice refers to any device capable of communicating via and/or as partof a network and may comprise a computing device. While network devicesmay be capable of communicating signals (e.g., signal packets and/orframes), such as via a wired and/or wireless network, they may also becapable of performing operations associated with a computing device,such as arithmetic and/or logic operations, processing and/or storingoperations (e.g., storing signal samples), such as in memory astangible, physical memory states, and/or may, for example, operate as aserver device and/or a client device in various embodiments. Networkdevices capable of operating as a server device, a client device and/orotherwise, may include, as examples, dedicated rack-mounted servers,desktop computers, laptop computers, set top boxes, tablets, netbooks,smart phones, wearable devices, integrated devices combining two or morefeatures of the foregoing devices, and/or the like, or any combinationthereof. As mentioned, signal packets and/or frames, for example, may beexchanged, such as between a server device and/or a client device, aswell as other types of devices, including between wired and/or wirelessdevices coupled via a wired and/or wireless network, for example, or anycombination thereof. It is noted that the terms, server, server device,server computing device, server computing platform and/or similar termsare used interchangeably. Similarly, the terms client, client device,client computing device, client computing platform and/or similar termsare also used interchangeably. While in some instances, for ease ofdescription, these terms may be used in the singular, such as byreferring to a “client device” or a “server device,” the description isintended to encompass one or more client devices and/or one or moreserver devices, as appropriate. Along similar lines, references to a“database” are understood to mean, one or more databases and/or portionsthereof, as appropriate.

It should be understood that for ease of description, a network device(also referred to as a networking device) may be embodied and/ordescribed in terms of a computing device and vice-versa. However, itshould further be understood that this description should in no way beconstrued so that claimed subject matter is limited to one embodiment,such as only a computing device and/or only a network device, but,instead, may be embodied as a variety of devices or combinationsthereof, including, for example, one or more illustrative examples.

A network may also include now known, and/or to be later developedarrangements, derivatives, and/or improvements, including, for example,past, present and/or future mass storage, such as network attachedstorage (NAS), a storage area network (SAN), and/or other forms ofdevice readable media, for example. A network may include a portion ofthe Internet, one or more local area networks (LANs), one or more widearea networks (WANs), wire-line type connections, wireless typeconnections, other connections, or any combination thereof. Thus, anetwork may be worldwide in scope and/or extent. Likewise, sub-networks,such as may employ differing architectures and/or may be substantiallycompliant and/or substantially compatible with differing protocols, suchas network computing and/or communications protocols (e.g., networkprotocols), may interoperate within a larger network.

In the context of the present patent application, the term sub-networkand/or similar terms, if used, for example, with respect to a network,refers to the network and/or a part thereof. Sub-networks may alsocomprise links, such as physical links, connecting and/or couplingnodes, so as to be capable to communicate signal packets and/or framesbetween devices of particular nodes, including via wired links, wirelesslinks, or combinations thereof. Various types of devices, such asnetwork devices and/or computing devices, may be made available so thatdevice interoperability is enabled and/or, in at least some instances,may be transparent. In the context of the present patent application,the term “transparent,” if used with respect to devices of a network,refers to devices communicating via the network in which the devices areable to communicate via one or more intermediate devices, such as of oneor more intermediate nodes, but without the communicating devicesnecessarily specifying the one or more intermediate nodes and/or the oneor more intermediate devices of the one or more intermediate nodesand/or, thus, may include within the network the devices communicatingvia the one or more intermediate nodes and/or the one or moreintermediate devices of the one or more intermediate nodes, but mayengage in signal communications as if such intermediate nodes and/orintermediate devices are not necessarily involved. For example, a routermay provide a link and/or connection between otherwise separate and/orindependent LANs.

In the context of the present patent application, a “private network”refers to a particular, limited set of devices, such as network devicesand/or computing devices, able to communicate with other devices, suchas network devices and/or computing devices, in the particular, limitedset, such as via signal packet and/or signal frame communications, forexample, without a need for re-routing and/or redirecting signalcommunications. A private network may comprise a stand-alone network;however, a private network may also comprise a subset of a largernetwork, such as, for example, without limitation, all or a portion ofthe Internet. Thus, for example, a private network “in the cloud” mayrefer to a private network that comprises a subset of the Internet.Although signal packet and/or frame communications (e.g. signalcommunications) may employ intermediate devices of intermediate nodes toexchange signal packets and/or signal frames, those intermediate devicesmay not necessarily be included in the private network by not being asource or designated destination for one or more signal packets and/orsignal frames, for example. It is understood in the context of thepresent patent application that a private network may direct outgoingsignal communications to devices not in the private network, but devicesoutside the private network may not necessarily be able to directinbound signal communications to devices included in the privatenetwork.

The Internet refers to a decentralized global network of interoperablenetworks that comply with the Internet Protocol (IP). It is noted thatthere are several versions of the Internet Protocol. The term InternetProtocol, IP, and/or similar terms are intended to refer to any version,now known and/or to be later developed. The Internet includes local areanetworks (LANs), wide area networks (WANs), wireless networks, and/orlong haul public networks that, for example, may allow signal packetsand/or frames to be communicated between LANs. The term World Wide Web(WWW or Web) and/or similar terms may also be used, although it refersto a part of the Internet that complies with the Hypertext TransferProtocol (HTTP). For example, network devices may engage in an HTTPsession through an exchange of appropriately substantially compatibleand/or substantially compliant signal packets and/or frames. It is notedthat there are several versions of the Hypertext Transfer Protocol. Theterm Hypertext Transfer Protocol, HTTP, and/or similar terms areintended to refer to any version, now known and/or to be laterdeveloped. It is likewise noted that in various places in this documentsubstitution of the term Internet with the term World Wide Web (“Web”)may be made without a significant departure in meaning and may,therefore, also be understood in that manner if the statement wouldremain correct with such a substitution.

Although claimed subject matter is not in particular limited in scope tothe Internet and/or to the Web; nonetheless, the Internet and/or the Webmay without limitation provide a useful example of an embodiment atleast for purposes of illustration. As indicated, the Internet and/orthe Web may comprise a worldwide system of interoperable networks,including interoperable devices within those networks. The Internetand/or Web has evolved to a public, self-sustaining facility accessibleto potentially billions of people or more worldwide. Also, in anembodiment, and as mentioned above, the terms “WWW” and/or “Web” referto a part of the Internet that complies with the Hypertext TransferProtocol. The Internet and/or the Web, therefore, in the context of thepresent patent application, may comprise a service that organizes storeddigital content, such as, for example, text, images, video, etc.,through the use of hypermedia, for example. It is noted that a network,such as the Internet and/or Web, may be employed to store electronicfiles and/or electronic documents.

The term electronic file and/or the term electronic document are usedthroughout this document to refer to a set of stored memory statesand/or a set of physical signals associated in a manner so as to therebyat least logically form a file (e.g., electronic) and/or an electronicdocument. That is, it is not meant to implicitly reference a particularsyntax, format and/or approach used, for example, with respect to a setof associated memory states and/or a set of associated physical signals.If a particular type of file storage format and/or syntax, for example,is intended, it is referenced expressly. It is further noted anassociation of memory states, for example, may be in a logical sense andnot necessarily in a tangible, physical sense. Thus, although signaland/or state components of a file and/or an electronic document, forexample, are to be associated logically, storage thereof, for example,may reside in one or more different places in a tangible, physicalmemory, in an embodiment.

A Hyper Text Markup Language (“HTML”), for example, may be utilized tospecify digital content and/or to specify a format thereof, such as inthe form of an electronic file and/or an electronic document, such as aWeb page, Web site, etc., for example. An Extensible Markup Language(“XML”) may also be utilized to specify digital content and/or tospecify a format thereof, such as in the form of an electronic fileand/or an electronic document, such as a Web page, Web site, etc., in anembodiment. Of course, HTML and/or XML are merely examples of “markup”languages, provided as non-limiting illustrations. Furthermore, HTMLand/or XML are intended to refer to any version, now known and/or to belater developed, of these languages. Likewise, claimed subject matterare not intended to be limited to examples provided as illustrations, ofcourse.

In the context of the present patent application, the term “Web site”and/or similar terms refer to Web pages that are associatedelectronically to form a particular collection thereof. Also, in thecontext of the present patent application, “Web page” and/or similarterms refer to an electronic file and/or an electronic documentaccessible via a network, including by specifying a uniform resourcelocator (URL) for accessibility via the Web, in an example embodiment.As alluded to above, in one or more embodiments, a Web page may comprisedigital content coded (e.g., via computer instructions) using one ormore languages, such as, for example, markup languages, including HTMLand/or XML, although claimed subject matter is not limited in scope inthis respect. Also, in one or more embodiments, application developersmay write code (e.g., computer instructions) in the form of JavaScript(or other programming languages), for example, executable by a computingdevice to provide digital content to populate an electronic documentand/or an electronic file in an appropriate format, such as for use in aparticular application, for example. Use of the term “JavaScript” and/orsimilar terms intended to refer to one or more particular programminglanguages are intended to refer to any version of the one or moreprogramming languages identified, now known and/or to be laterdeveloped. Thus, JavaScript is merely an example programming language.As was mentioned, claimed subject matter is not intended to be limitedto examples and/or illustrations.

In the context of the present patent application, the terms “entry,”“electronic entry,” “document,” “electronic document,” “content,”,“digital content,” “item,” and/or similar terms are meant to refer tosignals and/or states in a physical format, such as a digital signaland/or digital state format, e.g., that may be perceived by a user ifdisplayed, played, tactilely generated, etc. and/or otherwise executedby a device, such as a digital device, including, for example, acomputing device, but otherwise might not necessarily be readilyperceivable by humans (e.g., if in a digital format). Likewise, in thecontext of the present patent application, digital content provided to auser in a form so that the user is able to readily perceive theunderlying content itself (e.g., content presented in a form consumableby a human, such as hearing audio, feeling tactile sensations and/orseeing images, as examples) is referred to, with respect to the user, as“consuming” digital content, “consumption” of digital content,“consumable” digital content and/or similar terms. For one or moreembodiments, an electronic document and/or an electronic file maycomprise a Web page of code (e.g., computer instructions) in a markuplanguage executed or to be executed by a computing and/or networkingdevice, for example. In another embodiment, an electronic documentand/or electronic file may comprise a portion and/or a region of a Webpage. However, claimed subject matter is not intended to be limited inthese respects.

Also, for one or more embodiments, an electronic document and/orelectronic file may comprise a number of components. As previouslyindicated, in the context of the present patent application, a componentis physical, but is not necessarily tangible. As an example, componentswith reference to an electronic document and/or electronic file, in oneor more embodiments, may comprise text, for example, in the form ofphysical signals and/or physical states (e.g., capable of beingphysically displayed). Typically, memory states, for example, comprisetangible components, whereas physical signals are not necessarilytangible, although signals may become (e.g., be made) tangible, such asif appearing on a tangible display, for example, as is not uncommon.Also, for one or more embodiments, components with reference to anelectronic document and/or electronic file may comprise a graphicalobject, such as, for example, an image, such as a digital image, and/orsub-objects, including attributes thereof, which, again, comprisephysical signals and/or physical states (e.g., capable of being tangiblydisplayed). In an embodiment, digital content may comprise, for example,text, images, audio, video, and/or other types of electronic documentsand/or electronic files, including portions thereof, for example.

Also, in the context of the present patent application, the termparameters (e.g., one or more parameters) refer to material descriptiveof a collection of signal samples, such as one or more electronicdocuments and/or electronic files, and exist in the form of physicalsignals and/or physical states, such as memory states. For example, oneor more parameters, such as referring to an electronic document and/oran electronic file comprising an image, may include, as examples, timeof day at which an image was captured, latitude and longitude of animage capture device, such as a camera, for example, etc. In anotherexample, one or more parameters relevant to digital content, such asdigital content comprising a technical article, as an example, mayinclude one or more authors, for example. Claimed subject matter isintended to embrace meaningful, descriptive parameters in any format, solong as the one or more parameters comprise physical signals and/orstates, which may include, as parameter examples, collection name (e.g.,electronic file and/or electronic document identifier name), techniqueof creation, purpose of creation, time and date of creation, logicalpath if stored, coding formats (e.g., type of computer instructions,such as a markup language) and/or standards and/or specifications usedso as to be protocol compliant (e.g., meaning substantially compliantand/or substantially compatible) for one or more uses, and so forth.

Signal packet communications and/or signal frame communications, alsoreferred to as signal packet transmissions and/or signal frametransmissions (or merely “signal packets” or “signal frames”), may becommunicated between nodes of a network, where a node may comprise oneor more network devices and/or one or more computing devices, forexample. As an illustrative example, but without limitation, a node maycomprise one or more sites employing a local network address, such as ina local network address space. Likewise, a device, such as a networkdevice and/or a computing device, may be associated with that node. Itis also noted that in the context of this patent application, the term“transmission” is intended as another term for a type of signalcommunication that may occur in any one of a variety of situations.Thus, it is not intended to imply a particular directionality ofcommunication and/or a particular initiating end of a communication pathfor the “transmission” communication. For example, the mere use of theterm in and of itself is not intended, in the context of the presentpatent application, to have particular implications with respect to theone or more signals being communicated, such as, for example, whetherthe signals are being communicated “to” a particular device, whether thesignals are being communicated “from” a particular device, and/orregarding which end of a communication path may be initiatingcommunication, such as, for example, in a “push type” of signal transferor in a “pull type” of signal transfer. In the context of the presentpatent application, push and/or pull type signal transfers aredistinguished by which end of a communications path initiates signaltransfer.

Thus, a signal packet and/or frame may, as an example, be communicatedvia a communication channel and/or a communication path, such ascomprising a portion of the Internet and/or the Web, from a site via anaccess node coupled to the Internet or vice-versa. Likewise, a signalpacket and/or frame may be forwarded via network nodes to a target sitecoupled to a local network, for example. A signal packet and/or framecommunicated via the Internet and/or the Web, for example, may be routedvia a path, such as either being “pushed” or “pulled,” comprising one ormore gateways, servers, etc. that may, for example, route a signalpacket and/or frame, such as, for example, substantially in accordancewith a target and/or destination address and availability of a networkpath of network nodes to the target and/or destination address. Althoughthe Internet and/or the Web comprise a network of interoperablenetworks, not all of those interoperable networks are necessarilyavailable and/or accessible to the public.

In the context of the particular patent application, a network protocol,such as for communicating between devices of a network, may becharacterized, at least in part, substantially in accordance with alayered description, such as the so-called Open Systems Interconnection(OSI) seven layer type of approach and/or description. A networkcomputing and/or communications protocol (also referred to as a networkprotocol) refers to a set of signaling conventions, such as forcommunication transmissions, for example, as may take place betweenand/or among devices in a network. In the context of the present patentapplication, the term “between” and/or similar terms are understood toinclude “among” if appropriate for the particular usage and vice-versa.Likewise, in the context of the present patent application, the terms“compatible with,” “comply with” and/or similar terms are understood torespectively include substantial compatibility and/or substantialcompliance.

A network protocol, such as protocols characterized substantially inaccordance with the aforementioned OSI description, has several layers.These layers are referred to as a network stack. Various types ofcommunications (e.g., transmissions), such as network communications,may occur across various layers. A lowest level layer in a networkstack, such as the so-called physical layer, may characterize howsymbols (e.g., bits and/or bytes) are communicated as one or moresignals (and/or signal samples) via a physical medium (e.g., twistedpair copper wire, coaxial cable, fiber optic cable, wireless airinterface, combinations thereof, etc.). Progressing to higher-levellayers in a network protocol stack, additional operations and/orfeatures may be available via engaging in communications that aresubstantially compatible and/or substantially compliant with aparticular network protocol at these higher-level layers. For example,higher-level layers of a network protocol may, for example, affectdevice permissions, user permissions, etc.

A network and/or sub-network, in an embodiment, may communicate viasignal packets and/or signal frames, such via participating digitaldevices and may be substantially compliant and/or substantiallycompatible with, but is not limited to, now known and/or to bedeveloped, versions of any of the following network protocol stacks:ARCNET, AppleTalk, ATM, Bluetooth, DECnet, Ethernet, FDDI, Frame Relay,HIPPI, IEEE 1394, IEEE 802.11, IEEE-488, Internet Protocol Suite, IPX,Myrinet, OSI Protocol Suite, QsNet, RS-232, SPX, System NetworkArchitecture, Token Ring, USB, and/or X.25. A network and/or sub-networkmay employ, for example, a version, now known and/or later to bedeveloped, of the following: TCP/IP, UDP, DECnet, NetBEUI, IPX,AppleTalk and/or the like. Versions of the Internet Protocol (IP) mayinclude IPv4, IPv6, and/or other later to be developed versions.

Regarding aspects related to a network, including a communicationsand/or computing network, a wireless network may couple devices,including client devices, with the network. A wireless network mayemploy stand-alone, ad-hoc networks, mesh networks, Wireless LAN (WLAN)networks, cellular networks, and/or the like. A wireless network mayfurther include a system of terminals, gateways, routers, and/or thelike coupled by wireless radio links, and/or the like, which may movefreely, randomly and/or organize themselves arbitrarily, such thatnetwork topology may change, at times even rapidly. A wireless networkmay further employ a plurality of network access technologies, includinga version of Long Term Evolution (LTE), WLAN, Wireless Router (WR) mesh,2nd, 3rd, or 4th generation (2G, 3G, or 4G) cellular technology and/orthe like, whether currently known and/or to be later developed. Networkaccess technologies may enable wide area coverage for devices, such ascomputing devices and/or network devices, with varying degrees ofmobility, for example.

A network may enable radio frequency and/or other wireless typecommunications via a wireless network access technology and/or airinterface, such as Global System for Mobile communication (GSM),Universal Mobile Telecommunications System (UMTS), General Packet RadioServices (GPRS), Enhanced Data GSM Environment (EDGE), 3GPP Long TermEvolution (LTE), LTE Advanced, Wideband Code Division Multiple Access(WCDMA), Bluetooth, ultra-wideband (UWB), 802.11b/g/n, and/or the like.A wireless network may include virtually any type of now known and/or tobe developed wireless communication mechanism and/or wirelesscommunications protocol by which signals may be communicated betweendevices, between networks, within a network, and/or the like, includingthe foregoing, of course.

In one example embodiment, as shown in FIG. 19, a system embodiment maycomprise a local network (e.g., device 904 and medium 940) and/oranother type of network, such as a computing and/or communicationsnetwork. For purposes of illustration, therefore, FIG. 19 shows anembodiment 1900 of a system that may be employed to implement eithertype or both types of networks. Network 1908 may comprise one or morenetwork connections, links, processes, services, applications, and/orresources to facilitate and/or support communications, such as anexchange of communication signals, for example, between a computingdevice, such as 1902, and another computing device, such as 1906, whichmay, for example, comprise one or more client computing devices and/orone or more server computing device. By way of example, but notlimitation, network 1908 may comprise wireless and/or wiredcommunication links, telephone and/or telecommunications systems, Wi-Finetworks, Wi-MAX networks, the Internet, a local area network (LAN), awide area network (WAN), or any combinations thereof.

Example devices in FIG. 19 may comprise features, for example, of aclient computing device and/or a server computing device, in anembodiment. One or more computing devices, such as computing devices1902, 1904, and/or 1906, for example, may be utilized in variousembodiments, including example embodiments described herein inconnection with FIGS. 1-19. It is further noted that the term computingdevice, in general, whether employed as a client and/or as a server, orotherwise, refers at least to a processor and a memory connected by acommunication bus. Likewise, in the context of the present patentapplication at least, this is understood to refer to sufficientstructure within the meaning of 35 USC § 112 (f) so that it isspecifically intended that 35 USC § 112 (f) not be implicated by use ofthe term “computing device” and/or similar terms; however, if it isdetermined, for some reason not immediately apparent, that the foregoingunderstanding cannot stand and that 35 USC § 112 (f), therefore,necessarily is implicated by the use of the term “computing device”and/or similar terms, then, it is intended, pursuant to that statutorysection, that corresponding structure, material and/or acts forperforming one or more functions be understood and be interpreted to bedescribed at least in FIGS. 1-18, for example, and in the textassociated with the foregoing figure(s) of the present patentapplication.

An embodiment in accordance with claimed subject matter may include amethod of executing computer instructions on at least one computingdevice without further human interaction in which the at least onecomputing device includes at least one processor and at least onememory. An embodiment may include fetching computer instructions fromthe at least one memory of the at least one computing device forexecution on the at least one processor of the at least one computingdevice, executing the fetched computer instructions on the at least oneprocessor of the at least one computing device, and storing in the atleast one memory of the at least one computing device any results ofhaving executed the fetched computer instructions on the at least oneprocessor of the at least one computing device. In an embodiment, thecomputer instructions to be executed comprise instructions forprocessing epigenetic content, wherein executing the fetchedinstructions further includes obtaining epigenetic content for aparticular user representative of a plurality of particular epigeneticstates corresponding to respective points in time, tracking behavioralprofile content for the particular user over a period of time includingthe respective points in time, training a machine-learning device,system, or process, or a combination thereof, to identify one or morerelationships between one or more particular behaviors and one or morechanges in epigenetic state for the particular individual based, atleast in part, on the epigenetic content and the behavioral profilecontent, and identifying a further change in epigenetic state for theparticular individual based at least in part on a detected change inbehavioral profile content.

In an embodiment, an apparatus may include at least one computingdevice, the at least one computing device including at least oneprocessor and at least one memory, the at least one computing device toexecute computer instructions on the at least one processor withoutfurther human intervention. In an embodiment, the computer instructionsto be executed may be fetched from the at least one memory for executionon the at least one processor, and the at least one computing device maystore in the at least one memory of the at least one computing deviceany results to be generated from the execution on the at least oneprocessor of the to be executed computer instructions. In an embodiment,the computer instructions to be executed may include instructions forprocessing epigenetic content wherein the at least one processor toobtain epigenetic content for a particular user representative of aplurality of particular epigenetic states to correspond to respectivepoints in time, track behavioral profile content for the particular userover a period of time to include the respective points in time, train amachine-learning device, system, or process, or a combination thereof,to identify one or more relationships between one or more particularbehaviors and one or more changes in epigenetic state for the particularindividual based, at least in part, on the epigenetic content and thebehavioral profile content, and identify a further change in epigeneticstate for the particular individual based at least in part on a detectedchange in behavioral profile content.

Referring now again to FIG. 19, in an embodiment, first and thirddevices 1902 and 1906 may be capable of rendering a graphical userinterface (GUI) for a network device and/or a computing device, forexample, so that a user-operator may engage in system use. Device 1904may potentially serve a similar function in this illustration. Likewise,in FIG. 19, computing device 1902 (‘first device’ in figure) mayinterface with computing device 1904 (‘second device’ in figure), whichmay, for example, also comprise features of a client computing deviceand/or a server computing device, in an embodiment. Processor (e.g.,processing device) 1920 and memory 1922, which may comprise primarymemory 1924 and secondary memory 1926, may communicate by way of acommunication bus 1915, for example. The term “computing device,” in thecontext of the present patent application, refers to a system and/or adevice, such as a computing apparatus, that includes a capability toprocess (e.g., perform computations) and/or store digital content, suchas electronic files, parameters, electronic documents, measurements,text, images, video, audio, etc. in the form of signals and/or states.Thus, a computing device, in the context of the present patentapplication, may comprise hardware, software, firmware, or anycombination thereof (other than software per se). Computing device 1904,as depicted in FIG. 19, is merely one example, and claimed subjectmatter is not limited in scope to this particular example.

As mentioned, for one or more embodiments, a computing device maycomprise, for example, any of a wide range of digital electronicdevices, including, but not limited to, desktop and/or notebookcomputers, high-definition televisions, digital versatile disc (DVD)and/or other optical disc players and/or recorders, game consoles,satellite television receivers, cellular telephones, tablet devices,wearable devices, personal digital assistants, mobile audio and/or videoplayback and/or recording devices, or any combination of the foregoing.Further, unless specifically stated otherwise, a process as described,such as with reference to flow diagrams and/or otherwise, may also beexecuted and/or affected, in whole or in part, by a computing deviceand/or a network device. A device, such as a computing device and/ornetwork device, may vary in terms of capabilities and/or features.Claimed subject matter is intended to cover a wide range of potentialvariations. For example, a device may include a numeric keypad and/orother display of limited functionality, such as a monochrome liquidcrystal display (LCD) for displaying text, for example. In contrast,however, as another example, a web-enabled device may include a physicaland/or a virtual keyboard, mass storage, one or more accelerometers, oneor more gyroscopes, global positioning system (GPS) and/or otherlocation-identifying type capability, and/or a display with a higherdegree of functionality, such as a touch-sensitive color 2D or 3Ddisplay, for example.

As suggested previously, communications between a computing deviceand/or a network device and a wireless network may be in accordance withknown and/or to be developed network protocols including, for example,global system for mobile communications (GSM), enhanced data rate forGSM evolution (EDGE), 802.11b/g/n/h, etc., and/or worldwideinteroperability for microwave access (WiMAX). A computing device and/ora networking device may also have a subscriber identity module (SIM)card, which, for example, may comprise a detachable or embedded smartcard that is able to store subscription content of a user, and/or isalso able to store a contact list. A user may own the computing deviceand/or network device or may otherwise be a user, such as a primaryuser, for example. A device may be assigned an address by a wirelessnetwork operator, a wired network operator, and/or an Internet ServiceProvider (ISP). For example, an address may comprise a domestic orinternational telephone number, an Internet Protocol (IP) address,and/or one or more other identifiers. In other embodiments, a computingand/or communications network may be embodied as a wired network,wireless network, or any combinations thereof.

A computing and/or network device may include and/or may execute avariety of now known and/or to be developed operating systems,derivatives and/or versions thereof, including computer operatingsystems, such as Windows, iOS, Linux, a mobile operating system, such asiOS, Android, Windows Mobile, and/or the like. A computing device and/ornetwork device may include and/or may execute a variety of possibleapplications, such as a client software application enablingcommunication with other devices. For example, one or more messages(e.g., content) may be communicated, such as via one or more protocols,now known and/or later to be developed, suitable for communication ofemail, short message service (SMS), and/or multimedia message service(MMS), including via a network, such as a social network, formed atleast in part by a portion of a computing and/or communications network,including, but not limited to, Facebook, LinkedIn, Twitter, Flickr,and/or Google+, to provide only a few examples. A computing and/ornetwork device may also include executable computer instructions toprocess and/or communicate digital content, such as, for example,textual content, digital multimedia content, and/or the like. Acomputing and/or network device may also include executable computerinstructions to perform a variety of possible tasks, such as browsing,searching, playing various forms of digital content, including locallystored and/or streamed video, and/or games such as, but not limited to,fantasy sports leagues. The foregoing is provided merely to illustratethat claimed subject matter is intended to include a wide range ofpossible features and/or capabilities.

In FIG. 19, computing device 1902 may provide one or more sources ofexecutable computer instructions in the form physical states and/orsignals (e.g., stored in memory states), for example. Computing device1902 may communicate with computing device 1904 by way of a networkconnection, such as via network 1908, for example. As previouslymentioned, a connection, while physical, may not necessarily betangible. Although computing device 1904 of FIG. 19 shows varioustangible, physical components, claimed subject matter is not limited toa computing devices having only these tangible components as otherimplementations and/or embodiments may include alternative arrangementsthat may comprise additional tangible components or fewer tangiblecomponents, for example, that function differently while achievingsimilar results. Rather, examples are provided merely as illustrations.It is not intended that claimed subject matter be limited in scope toillustrative examples.

Memory 1922 may comprise any non-transitory storage mechanism. Memory1922 may comprise, for example, primary memory 1924 and secondary memory1926, additional memory circuits, mechanisms, or combinations thereofmay be used. Memory 1922 may comprise, for example, random accessmemory, read only memory, etc., such as in the form of one or morestorage devices and/or systems, such as, for example, a disk driveincluding an optical disc drive, a tape drive, a solid-state memorydrive, etc., just to name a few examples.

Memory 1922 may be utilized to store a program of executable computerinstructions. For example, processor 1920 may fetch executableinstructions from memory and proceed to execute the fetchedinstructions. Memory 1922 may also comprise a memory controller foraccessing device readable-medium 1940 that may carry and/or makeaccessible digital content, which may include code, and/or instructions,for example, executable by processor 1920 and/or some other device, suchas a controller, as one example, capable of executing computerinstructions, for example. Under direction of processor 1920, anon-transitory memory, such as memory cells storing physical states(e.g., memory states), comprising, for example, a program of executablecomputer instructions, may be executed by processor 1920 and able togenerate signals to be communicated via a network, for example, aspreviously described. Generated signals may also be stored in memory,also previously suggested.

Memory 1922 may store electronic files and/or electronic documents, suchas relating to one or more users, and may also comprise acomputer-readable medium that may carry and/or make accessible content,including code and/or instructions, for example, executable by processor1920 and/or some other device, such as a controller, as one example,capable of executing computer instructions, for example. As previouslymentioned, the term electronic file and/or the term electronic documentare used throughout this document to refer to a set of stored memorystates and/or a set of physical signals associated in a manner so as tothereby form an electronic file and/or an electronic document. That is,it is not meant to implicitly reference a particular syntax, formatand/or approach used, for example, with respect to a set of associatedmemory states and/or a set of associated physical signals. It is furthernoted an association of memory states, for example, may be in a logicalsense and not necessarily in a tangible, physical sense. Thus, althoughsignal and/or state components of an electronic file and/or electronicdocument, are to be associated logically, storage thereof, for example,may reside in one or more different places in a tangible, physicalmemory, in an embodiment.

Algorithmic descriptions and/or symbolic representations are examples oftechniques used by those of ordinary skill in the signal processingand/or related arts to convey the substance of their work to othersskilled in the art. An algorithm is, in the context of the presentpatent application, and generally, is considered to be a self-consistentsequence of operations and/or similar signal processing leading to adesired result. In the context of the present patent application,operations and/or processing involve physical manipulation of physicalquantities. Typically, although not necessarily, such quantities maytake the form of electrical and/or magnetic signals and/or statescapable of being stored, transferred, combined, compared, processedand/or otherwise manipulated, for example, as electronic signals and/orstates making up components of various forms of digital content, such assignal measurements, text, images, video, audio, etc.

It has proven convenient at times, principally for reasons of commonusage, to refer to such physical signals and/or physical states as bits,values, elements, parameters, symbols, characters, terms, numbers,numerals, measurements, content and/or the like. It should beunderstood, however, that all of these and/or similar terms are to beassociated with appropriate physical quantities and are merelyconvenient labels. Unless specifically stated otherwise, as apparentfrom the preceding discussion, it is appreciated that throughout thisspecification discussions utilizing terms such as “processing,”“computing,” “calculating,” “determining”, “establishing”, “obtaining”,“identifying”, “selecting”, “generating”, and/or the like may refer toactions and/or processes of a specific apparatus, such as a specialpurpose computer and/or a similar special purpose computing and/ornetwork device. In the context of this specification, therefore, aspecial purpose computer and/or a similar special purpose computingand/or network device is capable of processing, manipulating and/ortransforming signals and/or states, typically in the form of physicalelectronic and/or magnetic quantities, within memories, registers,and/or other storage devices, processing devices, and/or display devicesof the special purpose computer and/or similar special purpose computingand/or network device. In the context of this particular patentapplication, as mentioned, the term “specific apparatus” thereforeincludes a general purpose computing and/or network device, such as ageneral purpose computer, once it is programmed to perform particularfunctions, such as pursuant to program software instructions.

In some circumstances, operation of a memory device, such as a change instate from a binary one to a binary zero or vice-versa, for example, maycomprise a transformation, such as a physical transformation. Withparticular types of memory devices, such a physical transformation maycomprise a physical transformation of an article to a different state orthing. For example, but without limitation, for some types of memorydevices, a change in state may involve an accumulation and/or storage ofcharge or a release of stored charge. Likewise, in other memory devices,a change of state may comprise a physical change, such as atransformation in magnetic orientation. Likewise, a physical change maycomprise a transformation in molecular structure, such as fromcrystalline form to amorphous form or vice-versa. In still other memorydevices, a change in physical state may involve quantum mechanicalphenomena, such as, superposition, entanglement, and/or the like, whichmay involve quantum bits (qubits), for example. The foregoing is notintended to be an exhaustive list of all examples in which a change instate from a binary one to a binary zero or vice-versa in a memorydevice may comprise a transformation, such as a physical, butnon-transitory, transformation. Rather, the foregoing is intended asillustrative examples.

Referring again to FIG. 19, processor 1920 may comprise one or morecircuits, such as digital circuits, to perform at least a portion of acomputing procedure and/or process. By way of example, but notlimitation, processor 1920 may comprise one or more processors, such ascontrollers, microprocessors, microcontrollers, application specificintegrated circuits, digital signal processors, programmable logicdevices, field programmable gate arrays, the like, or any combinationthereof. In various implementations and/or embodiments, processor 1920may perform signal processing, typically substantially in accordancewith fetched executable computer instructions, such as to manipulatesignals and/or states, to construct signals and/or states, etc., withsignals and/or states generated in such a manner to be communicatedand/or stored in memory, for example.

FIG. 19 also illustrates device 1904 as including a component 1932operable with input/output devices, for example, so that signals and/orstates may be appropriately communicated between devices, such as device1904 and an input device and/or device 1904 and an output device. A usermay make use of an input device, such as a computer mouse, stylus, trackball, keyboard, and/or any other similar device capable of receivinguser actions and/or motions as input signals. Likewise, a user may makeuse of an output device, such as a display, a printer, etc., and/or anyother device capable of providing signals and/or generating stimuli fora user, such as visual stimuli, audio stimuli and/or other similarstimuli.

In the preceding description, various aspects of claimed subject matterhave been described. For purposes of explanation, specifics, such asamounts, systems and/or configurations, as examples, were set forth. Inother instances, well-known features were omitted and/or simplified soas not to obscure claimed subject matter. While certain features havebeen illustrated and/or described herein, many modifications,substitutions, changes and/or equivalents will now occur to thoseskilled in the art. It is, therefore, to be understood that the appendedclaims are intended to cover all modifications and/or changes as fallwithin claimed subject matter.

What is claimed is:
 1. An apparatus, comprising: at least onecommunication interface of at least one computing device to receivesignal packets from one or more external computing devices via anetwork; at least one processor of the at least one computing device to:obtain a plurality of signal packets received at the at least onecommunication interface to represent omic content or environmentalfactor content, or a combination thereof, for one or more users, whereinthe omic content to include one or more parameters indicative ofparticular bio-markers associated with particular gene expressions; andlogically and/or physically partition the signal packets representativeof the omic content into one or more bio-ledgers and the signal packetsrepresentative of the environmental factor content into one or morebiosphere ledgers; at least one memory of the at least one computingdevice to store the one or more bio-ledgers and the one or morebiosphere ledgers, wherein particular bio-ledger entries and particularbiosphere ledger entries to be accessible, at least in part, on aper-user basis, and wherein the particular bio-ledger entries to includea first set of particular authorizations with respect to read and/orwrite access for the particular bio-ledger entries, and wherein theparticular biosphere ledger entries to include a second set ofparticular authorizations with respect to read and/or write access forthe particular biosphere ledger entries; and wherein the at least oneprocessor to selectively authorize requests from one or more externaldevices to read from and/or write to the particular bio-ledger entriesand/or the particular biosphere ledger entries based, at least in part,on one or more security tokens provided by the one or more externaldevices and based, at least in part, on the first and/or second sets ofparticular authorizations, wherein the at least one communicationinterface and/or the at least one processor to detect connection of aportable computing device, wherein the at least one processor toinitiate transmission, via the at least one communication interface, ofone or more signal packets representative of one or more particularcommunication, security, and/or cryptographic parameters to the portablecomputing device at least in part in response to the detectedconnection, wherein the one or more particular communication, security,and/or cryptographic parameters to enable, at least in part, aparticular external device to read from and/or write to particularbio-ledger entries and/or particular biosphere ledger entries associatedwith a particular user.
 2. The apparatus of claim 1, wherein theenvironmental factor content to include content representative of one ormore environmental exposure parameters, one or more dietary consumptionparameters, one or more media consumption parameters, one or moreexercise and/or other lifestyle parameters, or behavioral profilecontent, or a combination thereof.
 3. The apparatus of claim 1, whereinthe particular biosphere ledger entries and/or the particular bio-ledgerentries to include parameters representative of particular points intime associated with particular environmental factor content.
 4. Theapparatus of claim 1, wherein the particular biosphere ledger entriesand/or the particular bio-ledger entries to include respectiveparameters indicative of particular locations associated with theparticular entries.
 5. The apparatus of claim 1, wherein the particularbiosphere ledger entries and/or the particular bio-ledger entries toinclude respective metric of influence parameters indicative of a degreeof relevance to the particular user and/or to include respectiveparameters indicative of a tangibility metric associated with theparticular biosphere ledger entries.
 6. The apparatus of claim 1,wherein the at least one communication interface to include an externaldevice port, wherein the at least one processor to initiate transmissionof the one or more particular communication, security, and/orcryptographic parameters at least in part in response to a physicalattachment of the portable computing device to the external device port.7. The apparatus of claim 6, wherein the at least one processor toencrypt the particular bio-ledger entries and/or biosphere ledgerentries.
 8. The apparatus of claim 7, wherein the one or more particularcryptographic parameters to include a decryption key to allow fordecryption of the particular bio-ledger entries associated with theparticular user and/or an encryption key to allow for encryption of omiccontent generated by the particular external device.
 9. The apparatus ofclaim 8, wherein the at least one processor to: obtain one or moresignal packets received at the at least one communication interface fromthe particular external device representative of a request to access oneor more of the particular bio-ledger entries and/or the particularbiosphere ledger entries associated with the particular user; andinitiate transmission, via the at least one communication interface, ofone or more signal packets representative of the one or more of theparticular bio-ledger entries and/or the particular biosphere ledgerentries associated with the particular user to the particular externaldevice at least in part in response to the request, wherein the requestto include a particular security token obtained by the particularexternal device from the portable computing device, wherein theparticular security token to comprise at least one of the one or moreparticular communication, security, and/or cryptographic parameters. 10.The apparatus of claim 1, wherein the at least one computing device tocomprise a secure storage device or the one or more external computingdevices to comprise one or more bio-smart devices, or a combinationthereof.
 11. A method, comprising: receiving, via at least onecommunication interface of at least one computing device from one ormore external computing devices via a network, a plurality of signalpackets representative of omic content or environmental factor content,or a combination thereof, for one or more users, wherein the omiccontent includes one or more parameters indicative of particularbio-markers associated with particular gene expressions; partitioning,logically and/or physically via at least one processor of the at leastone computing device, the signal packets representative of the omiccontent into one or more bio-ledgers and the signal packetsrepresentative of the environmental factor content into one or morebiosphere ledgers; storing in at least one memory of the computingdevice the one or more bio-ledgers and the one or more biosphereledgers, wherein particular bio-ledger entries and particular biosphereledger entries are accessible, at least in part, on a per-user basis,and wherein the particular bio-ledger entries include a first set ofparticular authorizations with respect to read and/or write access forthe particular bio-ledger entries, and wherein the particular biosphereledger entries include a second set of particular authorizations withrespect to read and/or write access for the particular biosphere ledgerentries; selectively authorizing, utilizing the at least one processor,requests obtained as signal packets via the network from one or moreexternal devices to read from and/or write to the particular bio-ledgerentries and/or the particular biosphere ledger entries based, at leastin part, on one or more security tokens provided by the one or moreexternal devices and based, at least in part, on the first and/or secondsets of particular authorizations; obtaining, via the communicationinterface from a particular external device of the one or more externaldevices, one or more signal packets representative of a request toaccess one or more particular bio-ledger entries and/or biosphere ledgerentries associated with a particular user of the one or more users; andtransmitting, via the communication interface, one or more signalpackets representative of the one or more of the particular bio-ledgerentries and/or biosphere ledger entries associated with the particularuser to the particular external device at least in part in response tothe request, wherein the request includes a particular security token ofthe one or more security tokens obtained by the particular externaldevice from a portable computing device, wherein the particular securitytoken comprises at least one of one or more particular communication,security, and/or cryptographic parameters to enable, at least in part,the particular external device to read from and/or write to the one ormore particular bio-ledger entries and/or biosphere ledger entriesassociated with the particular user.
 12. The method of claim 11, whereinthe environmental factor content includes content representative of oneor more environmental exposure parameters, one or more dietaryconsumption parameters, one or more media consumption parameters, one ormore exercise and/or other lifestyle parameters or behavioral profilecontent, or a combination thereof.
 13. The method of claim 11, whereinthe particular biosphere ledger entries and/or the particular bio-ledgerentries include parameters representative of particular points in timeassociated with particular environmental factor content.
 14. The methodof claim 11, wherein the particular biosphere ledger entries and/or theparticular bio-ledger entries include respective parameters indicativeof particular locations associated with the particular entries.
 15. Themethod of claim 11, wherein the particular biosphere ledger entriesand/or the particular bio-ledger entries include respective metric ofinfluence parameters indicative of a degree of relevance to theparticular user and/or include respective parameters indicative of atangibility metric associated with the particular biosphere ledgerentries.
 16. The method of claim 11, further comprising: detecting, viathe at least one communication interface, a connection of the portablecomputing device; and initiating transmission, by the at least oneprocessor via the communication interface, of one or more signal packetsrepresentative of the one or more particular communication, security,and/or cryptographic parameters to the portable computing device atleast in part in response to the detected connection.
 17. The method ofclaim 16, wherein the at least one communication interface includes anexternal device port, wherein the initiating transmission of the one ormore particular communication, security, and/or cryptographic parametersincludes initiating the transmission at least in part in response to aphysical attachment of the portable computing device to the externaldevice port.
 18. The method of claim 17, further comprising encryptingthe particular bio-ledger entries and/or the particular biosphere ledgerentries utilizing, at least in part, the at least one processor, andwherein the one or more particular cryptographic parameters to include adecryption key to allow for decryption of the particular bio-ledgerentries associated with the particular user and/or an encryption key toallow for encryption of omic content generated by the particularexternal device.
 19. An apparatus, comprising: at least onecommunication interface of at least one computing device to receivesignal packets from one or more external computing devices via anetwork, the at least one communication interface to include an externaldevice port; at least one processor of the at least one computing deviceto: obtain a plurality of signal packets received at the at least onecommunication interface to represent omic content or environmentalfactor content, or a combination thereof, for one or more users, whereinthe omic content to include one or more parameters indicative ofparticular bio-markers associated with particular gene expressions; andlogically and/or physically partition the signal packets representativeof the omic content into one or more bio-ledgers and the signal packetsrepresentative of the environmental factor content into one or morebiosphere ledgers; at least one memory of the at least one computingdevice to store the one or more bio-ledgers and the one or morebiosphere ledgers, wherein particular bio-ledger entries and particularbiosphere ledger entries to be accessible, at least in part, on aper-user basis, and wherein the particular bio-ledger entries to includea first set of particular authorizations with respect to read and/orwrite access for the particular bio-ledger entries, and wherein theparticular biosphere ledger entries to include a second set ofparticular authorizations with respect to read and/or write access forthe particular biosphere ledger entries; wherein the at least oneprocessor further to: detect physical attachment of a portable computingdevice to the external device port; initiate transmission, via the atleast one communication interface, of one or more signal packetsrepresentative of one or more particular communication, security, and/orcryptographic parameters to the portable computing device at least inpart in response to the detected physical attachment, wherein the one ormore particular communication, security, and/or cryptographic parametersto enable, at least in part, one or more particular external devices toread from and/or write to particular bio-ledger entries and/orparticular biosphere ledger entries associated with a particular user;and selectively authorize requests from the one or more particularexternal devices to read from and/or write to the particular bio-ledgerentries and/or the particular biosphere ledger entries associated withthe particular user based, at least in part, on one or more securitytokens provided by the one or more particular external devices andbased, at least in part, on the first and/or second sets of particularauthorizations.